In order to achieve the high performance, we need to have an efficient scheduling of a parallel program onto the processors in multiprocessor systems that minimizes the entire execution time. This problem of multiprocessor scheduling can be stated as finding a schedule for a general task graph to be executed on a multiprocessor system so that the schedule length can be minimize [10]. This scheduling problem is known to be NP- Hard. In multi processor task scheduling, we have a number of CPU’s on which a number of tasks are to be scheduled that the program’s execution time is minimized. According to [10], the tasks scheduling problem is a key factor for a parallel multiprocessor system to gain better performance. A task can be partitioned into a group of subtasks and represented as a DAG (Directed Acyclic Graph), so the problem can be stated as finding a schedule for a DAG to be executed in a parallel multiprocessor system so that the schedule can be minimized. This helps to reduce processing time and increase processor utilization. The aim of this thesis work is to check and compare the results obtained by Bee Colony algorithm with already generated best known results in multi processor task scheduling domain.