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Performance of Particle Swarm Optimization in Scheduling Hybrid Flow-Shops with Multiprocessor Tasks

  • M. Fikret Ercan
  • Yu-Fai Fung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4707)

Abstract

In many industrial and computing applications, proper scheduling of tasks can determine the overall efficiency of the system. The algorithm, presented in this paper, tackles the scheduling problem in a multi-layer multiprocessor environment, which exists in many computing and industrial applications. Based on the scheduling terminology, the problem can be defined as multiprocessor task scheduling in hybrid flow-shops. This paper presents a particle swarm optimization algorithm for the solution and reports its performance. The results are compared with other well known meta-heuristic techniques proposed for the solution of the same problem. Our results show that particle swarm optimization has merits in solving multiprocessor task scheduling in a hybrid flow-shop environment.

Keywords

Particle Swarm Optimization Schedule Problem Completion Time Tabu Search Particle Swarm Optimization Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • M. Fikret Ercan
    • 1
  • Yu-Fai Fung
    • 2
  1. 1.School of Electrical and Electronic Engineering, Singapore Polytechnic, 500 Dover Rd., S139651Singapore
  2. 2.Department of Electrical Engineering, Hong Kong Polytechnic University, Hung Hom Kowloon, Hong Kong SAR 

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