Using Bee Colony Optimization to Solve the Task Scheduling Problem in Homogenous Systems
Bee colony optimization (BCO) is one of the most recent algorithms in swarm intelligence that can be used in optimization problems this algorithm is based on the intelligent behavior of honey bees in foraging process. In this paper bee colony optimization is applied to solve the task scheduling problem which tasks have dependency with each other. Scheduling of tasks that represents by directed acyclic graph is a NP-complete problem. The main purpose of this problem is obtaining the minimum schedule length that is called make-span. To realize the performance of BCO in this problem, the obtained results are presented and compared with the most successful methods such as Ant colony system, Tabu search and simulate annealing. The comparison shows that BCO produces the solutions in a different way and it is still among the bests.
Keywords: Bee Colony Optimization, Task Graph, Task Scheduling Problem, Homogenous Processors
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ABOUT THE AUTHORS
Vahid Arabnejad
Department of Computer Engineering, Islamic Azad University, South branch Tehran, Iran
Ali Moeini
Computer Engineering Dept., University of Tehran Tehran, Iran,
Nasrollah Moghadam
Computer Engineering Dept., University of Tarbiat Modares Tehran, Iran
Vahid Arabnejad
Department of Computer Engineering, Islamic Azad University, South branch Tehran, Iran
Ali Moeini
Computer Engineering Dept., University of Tehran Tehran, Iran,
Nasrollah Moghadam
Computer Engineering Dept., University of Tarbiat Modares Tehran, Iran
