A hybrid particle swarm optimization algorithm for order planning problems of steel factory

Authors:
Tao Zhang;Zhifang Shao;Yuejie Zhang;Zhiwang Yu;Jianlin Jiang
Affiliations:
School of Information Management and Engineering, Shanghai University of Finance, and Economics, Shanghai, P.R China;School of Information Management and Engineering, Shanghai University of Finance, and Economics, Shanghai, P.R China;School of Computer Science, Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai, P.R China;School of Information Management and Engineering, Shanghai University of Finance, and Economics, Shanghai, P.R China;School of Information Management and Engineering, Shanghai University of Finance, and Economics, Shanghai, P.R China
Venue:
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2010

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Abstract

In this paper we construct an integer programming model for the order planning problem Our model takes into account inventory matching and production planning simultaneously, and considers multiple objectives We design a hybrid Particle Swarm Optimization, in which new heuristic rules to repair infeasible solutions are proposed, and then compare the results of using PSO, Tabu Search and the hybrid algorithm to solve the models of three different order quantities Numerical results show that the hybrid PSO/TS algorithm provides more effective solutions.