Nowadays in the world of mass consumption there is big demand for distribution centers of bigger size. Managing such a center is a very complex and difficult task regarding to the different processes and factors in a usual warehouse when we want to minimize the labor costs. Most of the workers’ working time is spent with traveling between source and destination points which cause deadheading. Even if a worker knows the structure of a warehouse well and because of that he or she can find the shortest path between two points, it is still not guaranteed that there won’t be long traveling time between the locations of two consecutive tasks. We need optimal assignments between tasks and workers. In the scientific literature Generalized Assignment Problem (GAP) is a wellknown problem which deals with the assignment of m workers to n tasks considering several constraints. The primary purpose of my thesis project was to choose a heuristics (genetic algorithm, tabu search or ant colony optimization) to be implemented into SAP Extended Warehouse Management (SAP EWM) by with task assignment will be more effective between tasks and resources. After system analysis I had to realize that due different constraints and business demands only 1:1 assingments are allowed in SAP EWM. Because of that I had to use a different and simpler approach – instead of the introduced heuristics – which could gain better assignments during the test phase in several cases. In the thesis I described in details what ware the most important questions and problems which emerged during the planning of my optimized assignment method.