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Journal of Intelligent Manufacturing

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01-06-2015

Hybrid particle swarm optimization and differential evolution algorithm for bi-level programming problem and its application to pricing and lot-sizing decisions

Authors: Weimin Ma, Miaomiao Wang, Xiaoxi Zhu

Published in: Journal of Intelligent Manufacturing | Issue 3/2015

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Abstract

This paper proposes a hierarchical hybrid particle swarm optimization (PSO) and differential evolution (DE) based algorithm (HHPSODE) to deal with bi-level programming problem (BLPP). To overcome the shortcomings of basic PSO and basic DE, this paper improves PSO and DE, respectively by using a velocity and position modulation method in PSO and a modified mutation strategy in DE. HHPSODE employs the modified PSO as a main program and the modified DE as a subprogram. According to the interactive iterations of modified PSO and DE, HHPSODE is independent of some restrictive conditions of BLPP. The results based on eight typical bi-level problems demonstrate that the proposed algorithm HHPSODE exhibits a better performance than other algorithms. HHPSODE is then adopted to solve a bi-level pricing and lot-sizing model proposed in this paper, and the data is used to analyze the features of the proposed bi-level model. Further tests based on the proposed bi-level model also exhibit good performance of HHPSODE in dealing with BLPP.

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Title: Hybrid particle swarm optimization and differential evolution algorithm for bi-level programming problem and its application to pricing and lot-sizing decisions
Authors: Weimin Ma
Miaomiao Wang
Xiaoxi Zhu
Publication date: 01-06-2015
Publisher: Springer US
Published in: Journal of Intelligent Manufacturing / Issue 3/2015
Print ISSN: 0956-5515
Electronic ISSN: 1572-8145
DOI: https://doi.org/10.1007/s10845-013-0803-5

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