Research of a Mold Job Shop Scheduling Optimization Based on Particle Swarm Optimization Algorithm

Author:

Lan Xiu Ju1,Su Dan Dan1

Affiliation:

1. Zhejiang University of Technology

Abstract

Job shop scheduling is a key part of production management and control for manufacturing enterprises. An optimized scheduling is helpful for enterprise to strengthen its efficiency and competition. And particle swarm optimization is a young algorithm of swarm intelligence. So application and research of job shop scheduling based on particle swarm optimization has important practical significance. This paper analyze and diagnose the scheduling status of a mold manufacturing workshop, taking minimize make span and average of AI based on fuzzy processing-time and delivery as optimizing target, model the scheduling for the manufacturing of CQD-035. Eventually, programming on the platform of MATLAB7.0.1 using the discrete particle swarm algorithm, a satisfactory scheduling scheme is obtained.

Publisher

Trans Tech Publications, Ltd.

Reference5 articles.

1. Jones, A. and Rabelo, J. C. Survey of Job Shop Scheduling Techniques, NISTIR, National Institute of Standards and technology. Gaithersbug. MD. Http: /www. mel. nist. gov/. 1998, 1-17.

2. Ling Wang. Shop scheduling and its genetic algorithm, First ed., Tsinghua University Press, Beijing, (2003).

3. Ling Wang, Bo Liu. Particle swarm optimization and scheduling algorithm, First ed. Tsinghua University Press, Beijing, (2008).

4. Slowinski R, Hapke M. Scheduling under fuzziness. [M]. New York: Physica-Verlag . (2000).

5. Ines Gonzalez-Rodriguez, Camino R. Vela. Study of Objective Functions in Fuzzy Job-Shop Problem. [M]. ICAISC 2006, LNAI 4029, 360-369.

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