General Particle Swarm Optimization Algorithm for Integration of Process Planning and Scheduling

Abstract:

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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 et al., "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:

$35.00

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