Task Scheduling Using Adaptive Weighted Particle Swarm Optimization with Adaptive Weighted Sum
G. Vidya, S. Sarathambekai, K. Umamaheswari, S.P. Yamunadevi · Procedia Engineering · 2012
Task scheduling is one of the core steps to effectively exploit the capabilities of parallel or distributed computing systems. Most existing approaches for scheduling deal with a single objective only. This paper presents an Adaptive Weighted Particle Swarm Optimization (AWPSO) algorithm with Adaptive Weighted Sum (AWS) method for multi-objective optimization problems in heterogeneous environment. AWPSO enhance the global search ability and to overcome the local optimum by introducing an acceleration factor. The goal is to minimize the make span and flow time. The experimental results showed that the performance of the AWPSO with adaptive weighted sum method is effective compared with AWPSO with weighted sum method in finding the optimal solutions.