Hybrid Particle Swarm Optimization for Permutation Flow Shop Scheduling

Author

Liu, Zhixiong ; Wang, Shaomei

Author_Institution

Coll. of Machinery & Autom., Wuhan Univ. of Sci. & Technol.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3245

Lastpage

3249

Abstract

Scheduling problem is a kind of well-known combination optimization problem, and many scheduling problems are NP problems. Particle swarm optimization is used to solve the permutation flow shop-scheduling problem. The particle representation based on particle position sequence is presented, which can ensure that the feasible scheduling solutions are made and is applicable to computational model of particle swam optimization. The local search method based on particle position crossing-over is introduced. The computational results prove that hybrid particle swarm optimization can effectively solve the permutation flow shop-scheduling problem, and outperforms genetic algorithm and NEH heuristic method

Keywords

computational complexity; flow shop scheduling; particle swarm optimisation; search problems; NP problem; combination optimization problem; hybrid particle swarm optimization; local search; particle position crossing-over; particle position sequence; permutation flow shop scheduling; Automation; Computational modeling; Educational institutions; Genetic algorithms; Job shop scheduling; Logistics; Machinery; Particle swarm optimization; Processor scheduling; Search methods; local search; particle representation; particle swarm optimization; scheduling;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712967

Filename

1712967