Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2012(Vol.4, Issue:22)
Article Information:

A New Cooperative Particle Swarm Optimizer and its Application in Permutation Flow Shop Scheduling Problem

Desheng Li and Na Deng
Corresponding Author:  Desheng Li 
Submitted: May 01, 2012
Accepted: May 22, 2012
Published: November 15, 2012
Abstract:
In this study, a new variant of Particle Swarm Optimization, Electoral Cooperative PSO (ECPSO), is presented and applied into solving the Permutation Flow Shop Scheduling Problem (PFSSP). Firstly, an electoral swarm is generated by the voting of primitive sub-swarms and also participates in evolution of swarm, whose particle candidates come from primitive sub-swarms with variable votes from them. Besides, a fast fitness computation method using processing time matrix of a valid schedule is also imported to accelerate the calculation of makespan function. On the other hand, in order to prevent trapping into local optimization, a disturbance factor mechanism is imported to check the particles movements for resetting the original subswarms and renewing the electoral swarm. To test the basic use and performance of ECPSO, some experiments on function optimization are executed on functions with unfixed and fixed numbers of dimensions. The proposed method was also applied to well-known benchmark of PFSSP, Taillard dataset; the results demonstrated good performances and robustness of ECPSO compared to some versions of PSO.

Key words:  Cooperative evolution , particle swarm optimization, permutation flow shop scheduling system, , , ,
Abstract PDF HTML
Cite this Reference:
Desheng Li and Na Deng, . A New Cooperative Particle Swarm Optimizer and its Application in Permutation Flow Shop Scheduling Problem. Research Journal of Applied Sciences, Engineering and Technology, (22): 4805-4812.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved