Paper Title:
General Particle Swarm Optimization Algorithm for Integration of Process Planning and Scheduling
  Abstract

To realize the integration of process planning and scheduling (IPPS) in the manufacturing system, a particle swarm optimization (PSO) algorithm is utilized. Based on the general PSO (GPSO) model, one GPSO algorithm is projected to solve IPPS. In GPSO, crossover and mutation operations of genetic algorithm are respectively used for particles to exchange information and search randomly, and tabu search (TS) is used for particles’ local search. And time varying crossover probability and time varying maximum step size of tabu search are introduced. Experimental results show that IPPS can be solved by GPSO effectively. The feasibility of the proposed GPSO model and the significance of the research on IPPS are also demonstrated.

  Info
Periodical
Advanced Materials Research (Volumes 118-120)
Edited by
L.Y. Xie, M.N. James, Y.X. Zhao and W.X. Qian
Pages
409-413
DOI
10.4028/www.scientific.net/AMR.118-120.409
Citation
S. T. Xu, X. Y. Li, L. Gao, Y. Sun, "General Particle Swarm Optimization Algorithm for Integration of Process Planning and Scheduling", Advanced Materials Research, Vols. 118-120, pp. 409-413, 2010
Online since
June 2010
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Price
$32.00
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