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  • 1.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    GRASP and statistical bounds for heuristic solutions to combinatorial problems2016Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few metaheuristics and combinatorial problems and, hence, the general performance of statistical bounds in combinatorial optimization remains an open question. This work complements the existing literature on statistical bounds by testing them on the metaheuristic Greedy Randomized Adaptive Search Procedures (GRASP) and four combinatorial problems. Our findings confirm previous results that statistical bounds are reliable for the p-median problem, while we note that they also seem reliable for the set covering problem. For the quadratic assignment problem, the statistical bounds has previously been found reliable when obtained from the Genetic algorithm whereas in this work they found less reliable. Finally, we provide statistical bounds to four 2-path network design problem instances for which the optimum is currently unknown.

  • 2.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Does Euclidean distance work well when the p-median model is applied in rural areas?2012Ingår i: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 201, nr 1, s. 83-97Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The p-median model is used to locate P centers to serve a geographically distributed population. A cornerstone of such a model is the measure of distance between a service center and demand points, i.e. the location of the population (customers, pupils, patients, and so on). Evidence supports the current practice of using Euclidean distance. However, we find that the location of multiple hospitals in a rural region of Sweden with anon-symmetrically distributed population is quite sensitive to distance measure, and somewhat sensitive to spatial aggregation of demand points.

  • 3.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Methodological issues in applying Location Models to Rural areas2010Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Location Models are usedfor planning the location of multiple service centers in order to serve a geographicallydistributed population. A cornerstone of such models is the measure of distancebetween the service center and a set of demand points, viz, the location of thepopulation (customers, pupils, patients and so on). Theoretical as well asempirical evidence support the current practice of using the Euclidian distancein metropolitan areas. In this paper, we argue and provide empirical evidencethat such a measure is misleading once the Location Models are applied to ruralareas with heterogeneous transport networks. This paper stems from the problemof finding an optimal allocation of a pre-specified number of hospitals in alarge Swedish region with a low population density. We conclude that the Euclidianand the network distances based on a homogenous network (equal travel costs inthe whole network) give approximately the same optimums. However networkdistances calculated from a heterogeneous network (different travel costs indifferent parts of the network) give widely different optimums when the numberof hospitals increases.  In terms ofaccessibility we find that the recent closure of hospitals and the in-optimallocation of the remaining ones has increased the average travel distance by 75%for the population. Finally, aggregation the population misplaces the hospitalsby on average 10 km.

  • 4.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik. Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Var ska sjukhusen ligga?2013Ingår i: Ekonomiska samfundets tidskrift, ISSN 0013-3183, E-ISSN 2323-1378, nr 3, s. 165-171Artikel i tidskrift (Refereegranskat)
    Abstract [sv]

    Denna artikel visar på en metod för att undersöka hur optimal befolkningens fysiska tillgänglighet till sjukvården är. Detta är relevant med tanke på den svenska storregionala omdaningen som säkerligen kommer provocera fram omprövningar av sjukhusens framtida placering.

    Med Dalarna som exempel fann vi att en ökning från dagens två till tre optimalt lokaliserade sjukhus skulle minska befolkningens genomsnittliga reseavstånd med 25 %.

    På basis av transportsektorns standardkalkyler för samhällsekonomisk effekter vid resande, samt av kostnader för drift av sjukvård sluter vi dessutom oss till att en komplettering av nuvarande två sjukhus i Dalarna med ett tredje vore samhällsekonomiskt effektivt.

  • 5.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik. Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Meng, Xiangli
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Rudholm, Niklas
    Högskolan Dalarna, Akademin Industri och samhälle, Nationalekonomi. HUI Research.
    Measuring CO2 emissions induced by online and brick-and-mortar retailing2014Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

  • 6.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik. Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Meng, Xiangli
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Rudholm, Niklas
    Högskolan Dalarna, Akademin Industri och samhälle, Nationalekonomi. HUI Research.
    Measuring CO2 emissions induced by online and brick-and-mortar retailing2014Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

  • 7.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik. Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Meng, Xiangli
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Rudholm, Niklas
    Högskolan Dalarna, Akademin Industri och samhälle, Nationalekonomi.
    Measuring transport related CO2 emissions induced by online and brick-and-mortar retailing2015Ingår i: Transportation Research Part D: Transport and Environment, ISSN 1361-9209, E-ISSN 1879-2340, Vol. 40, s. 28-42Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We develop a method for empirically measuring the difference in transport related carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their transport CO2 footprints by 84% when buying standard consumer electronics products. 

  • 8.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Rebreyend, Pascal
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    An empirical test of the gravity p-median model2012Rapport (Övrigt vetenskapligt)
    Abstract [en]

    A customer is presumed to gravitate to a facility by the distance to it and the attractiveness of it. However regarding the location of the facility, the presumption is that the customer opts for the shortest route to the nearest facility.This paradox was recently solved by the introduction of the gravity p-median model. The model is yet to be implemented and tested empirically. We implemented the model in an empirical problem of locating locksmiths, vehicle inspections, and retail stores ofv ehicle spare-parts, and we compared the solutions with those of the p-median model. We found the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

  • 9.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Rebreyend, Pascal
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Distance measure and the p-median problem in rural areas2012Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

  • 10.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik.
    Rebreyend, Pascal
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Distance measure and the p-median problem in rural areas2015Ingår i: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 226, nr 1, s. 89-99Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region with a sparse, heterogeneous network and a non-symmetric distribution of the population. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (1-100 facilities). We find that the network distance give as good a solution as the travel-time network. The Euclidean distance gives solutions some 4-10 per cent worse than the network distances, and the solutions tend to deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

  • 11.
    Carling, Kenneth
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik.
    Rebreyend, Pascal
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Testing the gravity p-median model empirically2015Ingår i: Operations Research Perspectives, ISSN 2214-7160, Vol. 2, nr 124, artikel-id 132Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced gravity p-median model offers an extension to the p-median model that account for this. The model is therefore potentially interesting, although it has not yet been implemented and tested empirically. In this paper, we have implemented the model in an empirical problem of locating vehicle inspections, locksmiths, and retail stores of vehicle spare-parts for the purpose of investigating its superiority to the p-median model. We found, however, the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

  • 12. Gu, Yaxiu
    et al.
    Zhang, Xingxing
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Myhren, Jonn Are
    Högskolan Dalarna, Akademin Industri och samhälle, Byggteknik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Chen, Xiangjie
    Yuan, Yanping
    Techno-economic analysis of a solar photovoltaic/thermal (PV/T) concentrator for building application in Sweden using Monte Carlo method2018Ingår i: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 165, s. 8-24Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The solar energy share in Sweden will grow up significantly in next a few decades. Such transition offers not only great opportunity but also uncertainties for the emerging solar photovoltaic/thermal (PV/T) technologies. This paper therefore aims to conduct a techno-economic evaluation of a reference solar PV/T concentrator in Sweden for building application. An analytical model is developed based on the combinations of Monte Carlo simulation techniques and multi energy-balance/financial equations, which takes into account of the integrated uncertainties and risks of various variables. In the model, 11 essential input variables, i.e. average daily solar irradiance, electrical/thermal efficiency, prices of electricity/heating, operation & management (OM) cost, PV/T capital cost, debt to equity ratio, interest rate, discount rate, and inflation rate, are considered, while the economic evaluation metrics, such as levelized cost of energy (LCOE), net present value (NPV), and payback period (PP), are primarily assessed. According to the analytical results, the mean values of LCOE, NPV and PP of the reference PV/T connector are observed at 1.27 SEK/kW h (0.127 €/kW h), 18,812.55 SEK (1881.255 €) and 10 years during its 25 years lifespan, given the project size at 10.37 m2 and capital cost at 4482–5378 SEK/m2 (448.2–537.8 €/m2). The positive NPV indicates that the investment on the selected PV/T concentrator will be profitable as the projected earnings exceeds the anticipated costs, depending on the NPV decision rule. The sensitivity analysis and the parametric study illustrate that the economic performance of the reference PV/T concentrator in Sweden is mostly proportional to solar irradiance, debt to equity ratio and heating price, but disproportionate to capital cost and discount rate. Together with additional market analysis of PV/T technologies in Sweden, it is expected that this paper could clarify the economic situation of PV/T technologies in Sweden and provide a useful model for their further investment decisions, in order to achieve sustainable and low-carbon economics, with an expanded quantitative discussion of the real economic or policy scenarios that may lead to those outcomes.

  • 13.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Computational study of the step size parameter of the subgradient optimization methodManuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    The subgradient optimization method is a simple and flexible linear programming iterative algorithm. It is much simpler than Newton's method and can be applied to a wider variety of problems. It also converges when the objective function is non-differentiable. Since an efficient algorithm will not only produce a good solution but also take less computing time, we always prefer a simpler algorithm with high quality. In this study a series of step size parameters in the subgradient equation is studied. The performance is compared for a general piecewise function and a specific p-median problem. We examine how the quality of solution changes by setting five forms of step size parameter.

  • 14.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Heuristic optimization of the p-median problem and population re-distribution2013Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    This thesis contributes to the heuristic optimization of the p-median problem and Swedish population redistribution.  

    The p-median model is the most representative model in the location analysis. When facilities are located to a population geographically distributed in Q demand points, the p-median model systematically considers all the demand points such that each demand point will have an effect on the decision of the location. However, a series of questions arise. How do we measure the distances? Does the number of facilities to be located have a strong impact on the result? What scale of the network is suitable? How good is our solution? We have scrutinized a lot of issues like those. The reason why we are interested in those questions is that there are a lot of uncertainties in the solutions. We cannot guarantee our solution is good enough for making decisions. The technique of heuristic optimization is formulated in the thesis.  

    Swedish population redistribution is examined by a spatio-temporal covariance model. A descriptive analysis is not always enough to describe the moving effects from the neighbouring population. A correlation or a covariance analysis is more explicit to show the tendencies. Similarly, the optimization technique of the parameter estimation is required and is executed in the frame of statistical modeling. 

  • 15.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Carling, Kenneth
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    GRASP and Statistical Bounds for Heuristic Solutions to Combinatorial Problems2019Ingår i: International Journal of Management and Applied Science, ISSN 2394-7926, Vol. 5, nr 8, s. 113-119Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few heuristics and combinatorial problems and, hence, the general performance of statistical bounds in combinatorial optimization remains an open question. This work complements the existing literature on statistical bounds by testing them on the metaheuristic Greedy Randomized Adaptive Search Procedures (GRASP) and four combinatorial problems. Our findings confirm previous results that statistical bounds are reliable for the p-median problem, while we note that they also seem reliable for the set covering problem. For the quadratic assignment problem, the statistical bounds have previously been found reliable when obtained from the Genetic algorithm whereas in this work they have been found less reliable. Finally, we provide statistical bounds to four 2-path network design problem instances for which the optimum is currently unknown.

  • 16.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Lundmark, M.
    Intra-urban location of stores and labour turnover in retail2019Ingår i: International Review of Retail Distribution & Consumer Research, ISSN 0959-3969, E-ISSN 1466-4402, Vol. 29, nr 4, s. 359-375Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The aim of this paper is to analyse labour turnover in retail firms with stores in different city locations. This case study of a Swedish mid-sized city uses comprehensive longitudinal register data on individuals. In a first step, an unconditional descriptive analysis shows that labour turnover in retail is higher in out-of-town locations, compared to more central locations in the city. In a second step, a generalized linear model (GLM) analysis is conducted where labour turnover in downtown and out-of-town locations are compared. Firm internal and industry factors, as well as employee characteristics, and location-specific factors are controlled for. The results indicate that commuting costs and intra-urban location have no statistically significant effect on labour turnover in retail firms. Instead, firm internal factors, such as human resource management, has a major influence on labour turnover rates. The findings indicate that in particular firms with multiple locations may need to pay extra attention to work conditions across stores in different places in a city, in order to avoid diverging levels of labour mobility. This paper complements previous survey-based studies on labour turnover by using a comprehensive micro-level dataset to analyse revealed rather than stated preferences concerning job-to-job mobility. An elaborated measure of labour turnover is used to analyse differences between shopping areas in different locations within the city. The particular research design used in this paper makes it possible to isolate the effect of intra-organizational conditions by analysing mobility within firms with workplaces in both downtown and out-of-town locations. This is the first comprehensive study of labour turnover and mobility with an intra-urban perspective in the retail sector.

  • 17.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Humaniora och medier, Kulturvetenskap.
    Rebreyend, Pascal
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    How do different densities in a network affect the optimal location of service centers?2013Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed. 

  • 18.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik.
    Rebreyend, Pascal
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    How does data quality in a network affect heuristic solutions?2014Rapport (Övrigt vetenskapligt)
    Abstract [en]

    To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used

    p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p).

    The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited

    improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low

    p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.

  • 19.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Rebreyend, Pascal
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    How does the use of different road networks effect the optimal location of facilities in rural areas?2012Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure.

    Distance measure can vary if the accuracy of the road network varies. The rst aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to nd an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using dierent algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with an asymmetrically distributed population, Dalecarlia.

    The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is optimized for. It is also shown that the simulated annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better location solutions.

  • 20.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    How do neighbouring populations affect local population change over time?2013Rapport (Övrigt vetenskapligt)
    Abstract [en]

    This study covers a period when society changed from a pre-industrial agricultural society to a post-industrial service-producing society. Parallel with this social transformation, major population changes took place. In this study, we analyse how local population changes are affected by neighbouring populations. To do so we use the last 200 years of local population change that redistributed population in Sweden. We use literature to identify several different processes and spatial dependencies in the redistribution between a parish and its surrounding parishes. The analysis is based on a unique unchanged historical parish division, and we use an index of local spatial correlation to describe different kinds of spatial dependencies that have influenced the redistribution of the population. To control inherent time dependencies, we introduce a non-separable spatial temporal correlation model into the analysis of population redistribution. Hereby, several different spatial dependencies can be observed simultaneously over time. The main conclusions are that while local population changes have been highly dependent on the neighbouring populations in the 19th century, this spatial dependence have become insignificant already when two parishes is separated by 5 kilometres in the late 20th century. Another conclusion is that the time dependency in the population change is higher when the population redistribution is weak, as it currently is and as it was during the 19th century until the start of industrial revolution.

  • 21.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. HUI Research.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik. Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi. HUI Research, Stockholm.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. HUI Research, Stockholm.
    To what extent do neighbouring populations affect local population growth over time?2016Ingår i: Population, Space and Place, ISSN 1544-8444, E-ISSN 1544-8452, Vol. 22, nr 1, s. 68-83Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This study covers a period when society changed from a pre-industrial agricultural society to a post-industrial service-producing society. Parallel with this social transformation, major population changes took place. In this study, we analyse to what extent local population change is affected by neighbouring populations. To do this, we focused on the last 190 years of local population change that redistributed population in Sweden. We used literature to identify several different processes in the population redistribution. The different processes implied different spatial dependencies between local population change and the surrounding populations. The analysis is based on an unchanged historical parish division, and we used an index of local spatial correlation to describe different types of spatial dependencies that influenced the redistribution of the population. To control inherent time dependencies, we introduced a non-separable spatial-temporal correlation model into the analysis of population redistribution. Hereby, several different spatial dependencies could be simultaneously observed over time. The main conclusions are that while local population changes have been highly dependent on neighbouring populations in the 19th century, this spatial dependence became insignificant already when two parishes are separated by 5 km in the late 20th century. It is argued that the only process that significantly redistributed the population at the end of the 20th century is the immigration to Sweden.

  • 22.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    May, Ross
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Zhang, Xingxing
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Wang, Xinru
    Pan, Song
    Yan, Da
    Jin, Yuan
    A novel reinforcement learning method for improving occupant comfort via window opening and closingManuskript (preprint) (Övrigt vetenskapligt)
  • 23.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    May, Ross
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Zhang, Xingxing
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Wang, Xinru
    Pan, Song
    Yan, Da
    Jin, Yuan
    Xu, Liguo
    A review of reinforcement learning methodologies for controlling occupant comfort in buildings2019Ingår i: Sustainable cities and society, ISSN 2210-6707, Vol. 51, artikel-id 101748Artikel i tidskrift (Refereegranskat)
  • 24.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Mihaescu, Oana
    HUI Research, Sweden.
    Li, Yujiao
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Rudholm, Niklas
    Högskolan Dalarna, Akademin Industri och samhälle, Nationalekonomi. HUI Research, Sweden.
    Comparison and one-stop shopping after big-box retail entry: a spatial difference-in-difference analysis2018Ingår i: Journal of Retailing and Consumer Services, ISSN 0969-6989, E-ISSN 1873-1384, Vol. 40, s. 175-187Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper empirically measures the potential spillover effects of big-box retail entry on the productivity of incumbent retailers in the entry regions, and investigates whether the effects differ depending on 1) if the entry is in a rural or urban area, and 2) if the incumbent retailers are within retail industries selling substitute or complement goods to those found in IKEA. To identify the IKEA-entry effect, a difference-in-difference model is suitable, but traditionally such estimators neglect the possibility that firms’ sales are determined by a process with spatially interactive responses. If ignored, these responses may cause biased estimates of the IKEA entry effect due to spatial heterogeneity of the treatment effect. One objective of this paper is thus to propose a spatial difference-in-difference estimator accounting for possible spatial spillover effects of IKEA entry. Particular emphasis is placed on the development of a suitable weight matrix accounting for the spatial links between firms, where we allow for local spatial interactions such that the outcome of observed units depends both on their own treatment as well as on the treatment of their neighbors. Our results show that for complementary goods retailers (or one-stop shopping retailers) in Haparanda and Kalmar, productivity increased by 35% and 18%, respectively, due to IKEA entry. No statistically significant effects were found for the entries in Karlstad and Gothenburg, indicating that it is mainly incumbents in smaller entry regions that benefit from IKEA entry. Also, for incumbent retailers selling substitute (or comparison shopping) goods no significant effects were found in any of the entry regions, indicating that it is mainly retailers selling complementary goods that benefit from IKEA entry. Finally, our results also show that ignoring the possibility of spatially correlated treatment effects in the regression models reduces the estimated impact of the IKEA entries in Haparanda and Kalmar on productivity in one-stop shopping retail firms with 3% and 0.1% points, respectively. © 2017 Elsevier Ltd

  • 25.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Zhang, Xingxing
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Xu, Liguo
    May, Ross
    Pan, Song
    Wu, Jinshun
    A review of reinforcement learning methodologies on control systems for building energy2018Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The usage of energy directly leads to a great amount of consumption of the non-renewable fossil resources. Exploiting fossil resources energy can influence both climate and health via ineluctable emissions. Raising awareness, choosing alternative energy and developing energy efficient equipment contributes to reducing the demand for fossil resources energy, but the implementation of them usually takes a long time. Since building energy amounts to around one-third of global energy consumption, and systems in buildings, e.g. HVAC, can be intervened by individual building management, advanced and reliable control techniques for buildings are expected to have a substantial contribution to reducing global energy consumptions. Among those control techniques, the model-free, data-driven reinforcement learning method seems distinctive and applicable. The success of the reinforcement learning method in many artificial intelligence applications has brought us an explicit indication of implementing the method on building energy control. Fruitful algorithms complement each other and guarantee the quality of the optimisation. As a central brain of smart building automation systems, the control technique directly affects the performance of buildings. However, the examination of previous works based on reinforcement learning methodologies are not available and, moreover, how the algorithms can be developed is still vague. Therefore, this paper briefly analyses the empirical applications from the methodology point of view and proposes the future research direction.

  • 26.
    Håkansson, Johan
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Carling, Kenneth
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Does euclidian distance work when location models are applied in rural areas?2010Rapport (Övrigt vetenskapligt)
  • 27. Li, Y
    et al.
    Rezgui, Y
    Guerriero, A
    Zhang, Xingxing
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Kubicki, S
    Yan, D
    Development of an adaptation table to enhance the accuracy of the predicted mean vote model2020Ingår i: Building and Environment, ISSN 0360-1323, E-ISSN 1873-684X, Vol. 168, artikel-id 106504Artikel i tidskrift (Refereegranskat)
  • 28. Pan, S
    et al.
    Xiong, Y
    Han, Y
    Zhang, Xingxing
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Xia, L
    Wei, S
    Wu, J
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    A study on influential factors of occupant window-opening behavior in an office building in China2018Ingår i: Building and Environment, ISSN 0360-1323, E-ISSN 1873-684X, Vol. 133, s. 41-50Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Occupants often perform many types of behavior in buildings to adjust the indoor thermal environment. In these types, opening/closing the windows, often regarded as window-opening behavior, is more commonly observed because of its convenience. It not only improves indoor air quality to satisfy occupants' requirement for indoor thermal comfort but also influences building energy consumption. To learn more about potential factors having effects on occupants' window-opening behavior, a field study was carried out in an office building within a university in Beijing. Window state (open/closed) for a total of 5 windows in 5 offices on the second floor in 285 days (9.5 months) were recorded daily. Potential factors, categorized as environmental and non-environmental ones, were subsequently identified with their impact on window-opening behavior through logistic regression and Pearson correlation approaches. The analytical results show that occupants' window-opening behavior is more strongly correlated to environmental factors, such as indoor and outdoor air temperatures, wind speed, relative humidity, outdoor FM2.5 concentrations, solar radiation, sunshine hours, in which air temperatures dominate the influence. While the non-environmental factors, i.e. seasonal change, time of day and personal preference, also affects the patterns of window-opening probability. This paper provides solid field data on occupant window opening behavior in China, with high resolutions and demonstrates the way in analyzing and predicting the probability of window-opening behavior. Its discussion into the potential impact factors shall be useful for further investigation of the relationship between building energy consumption and window-opening behavior.

  • 29.
    Rebreyend, Pascal
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    How does different algorithm work when applied on the different road networks when optimal location of facilities is searched for in rural areas?2014Ingår i: Web Information Systems Engineering – WISE 2013 Workshops: WISE 2013 International Workshops BigWebData, MBC, PCS, STeH, QUAT, SCEH, and STSC 2013, Nanjing, China, October 13-15, 2013, Revised Selected Papers / [ed] Zhisheng Huang, Chengfei Liu, Jing He, Guangyan Huang, Berlin: Springer Berlin/Heidelberg, 2014, Vol. 8182, s. 284-291Konferensbidrag (Refereegranskat)
    Abstract [en]

    The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure. The first aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to find an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using different algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with a. asymmetrically distributed population, Dalecarlia. The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is opt for. It is also shown that the Simulating annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better solutions.

  • 30. Wei, Yixuan
    et al.
    Xia, Liang
    Pan, Song
    Wu, Jinshun
    Zhang, Xingxing
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Zhang, Weiya
    Xie, Jingchao
    Li, Qingping
    Prediction of occupancy level and energy consumption in office building using blind system identification and neural networks2019Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 240, s. 276-294Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Occupancy behaviour plays an important role in energy consumption in buildings. Currently, the shallow understanding of occupancy has led to a considerable performance gap between predicted and measured energy use. This paper presents an approach to estimate the occupancy based on blind system identification (BSI), and a prediction model of electricity consumption by an air-conditioning system is developed and reported based on an artificial neural network with the BSI estimation of the number of occupants as an input. This starts from the identification of indoor CO2 dynamics derived from the mass-conservation law and venting levels. The unknown parameters, including the occupancy and model parameters, are estimated by using a frequentist maximum-likelihood algorithm and Bayesian estimation. The second phase is to establish the prediction model of the electricity consumption of the air-conditioning system by using a feed-forward neural network (FFNN) and extreme learning machine (ELM), as well as ensemble models. To analyse some aspects of the benchmark test for identifying the effect of structure parameters and input-selection alternatives, three studies are conducted on (1) the effect of predictor selection based on principal component analysis, (2) the effect of the estimated occupancy as the supplementary input, and (3) the effect of the neural network ensemble. The result shows that the occupancy number, as the input, is able to improve the accuracy in predicting energy consumption using a neural network model.

  • 31. Wei, Yixuan
    et al.
    Zhang, Xingxing
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Shi, Yong
    Xia, Liang
    Pan, Song
    Wu, Jinshun
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Zhao, Xiaoyun
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    A review of data-driven approaches for prediction and classification of building energy consumption2018Ingår i: Renewable & sustainable energy reviews, ISSN 1364-0321, E-ISSN 1879-0690, Vol. 82, nr 1, s. 1027-1047Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A recent surge of interest in building energy consumption has generated a tremendous amount of energy data, which boosts the data-driven algorithms for broad application throughout the building industry. This article reviews the prevailing data-driven approaches used in building energy analysis under different archetypes and granularities, including those methods for prediction (artificial neural networks, support vector machines, statistical regression, decision tree and genetic algorithm) and those methods for classification (K-mean clustering, self-organizing map and hierarchy clustering). The review results demonstrate that the data-driven approaches have well addressed a large variety of building energy related applications, such as load forecasting and prediction, energy pattern profiling, regional energy-consumption mapping, benchmarking for building stocks, global retrofit strategies and guideline making etc. Significantly, this review refines a few key tasks for modification of the data-driven approaches in the context of application to building energy analysis. The conclusions drawn in this review could facilitate future micro-scale changes of energy use for a particular building through the appropriate retrofit and the inclusion of renewable energy technologies. It also paves an avenue to explore potential in macro-scale energy-reduction with consideration of customer demands. All these will be useful to establish a better long-term strategy for urban sustainability.

  • 32.
    Zhang, Xingxing
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Lovati, Marco
    Vigna, Ilaria
    Widén, Joakim
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Gál, Csilla V
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Feng, Tao
    A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions2018Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 230, s. 1034-1056Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The emergence of renewable-energy-source (RES) envelope solutions, building retrofit requirements and advanced energy technologies brought about challenges to the existing paradigm of urban energy systems. It is envisioned that the building cluster approach—that can maximize the synergies of RES harvesting, building performance, and distributed energy management—will deliver the breakthrough to these challenges. Thus, this paper aims to critically review urban energy systems at the cluster level that incorporate building integrated RES solutions. We begin with defining cluster approach and the associated boundaries. Several factors influencing energy planning at cluster scale are identified, while the most important ones are discussed in detail. The closely reviewed factors include RES envelope solutions, solar energy potential, density of buildings, energy demand, integrated cluster-scale energy systems and energy hub. The examined categories of RES envelope solutions are (i) the solar power, (ii) the solar thermal and (iii) the energy-efficient ones, out of which solar energy is the most prevalent RES. As a result, methods assessing the solar energy potentials of building envelopes are reviewed in detail. Building density and the associated energy use are also identified as key factors since they affect the type and the energy harvesting potentials of RES envelopes. Modelling techniques for building energy demand at cluster level and their coupling with complex integrated energy systems or an energy hub are reviewed in a comprehensive way. In addition, the paper discusses control and operational methods as well as related optimization algorithms for the energy hub concept. Based on the findings of the review, we put forward a matrix of recommendations for cluster-level energy system simulations aiming to maximize the direct and indirect benefits of RES envelope solutions. By reviewing key factors and modelling approaches for characterizing RES-envelope-solutions-based urban energy systems at cluster level, this paper hopes to foster the transition towards more sustainable urban energy systems.

  • 33.
    Zhang, Xingxing
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Energiteknik.
    Wu, J.
    Pan, S.
    Han, Mengjie
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    An economic analysis of the solar photovoltaic/thermal (PV/T) technologies in Sweden: A case study2019Ingår i: IOP Conference Series: Materials Science and Engineering, 2019, Vol. 556, nr 1, artikel-id 012002Konferensbidrag (Refereegranskat)
1 - 33 av 33
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