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JACIII Vol.19 No.3 pp. 359-364
doi: 10.20965/jaciii.2015.p0359
(2015)

Paper:

Hybrid Genetic Algorithm Based on Chaotic Migration Strategy for Solving Flow Shop Scheduling Problem with Fuzzy Delivery Time

Wen-Zhan Dai and Kai Xia

School of Information and Electronic Engineering, Zhejiang Gongshang University
Hangzhou 310018, China

Received:
December 15, 2013
Accepted:
February 2, 2015
Published:
May 20, 2015
Keywords:
flow shop scheduling problem, genetic algorithm, chaotic migration, fuzzy delivery time
Abstract

In this paper, a hybrid genetic algorithm based on a chaotic migration strategy (HGABCM) for solving the flow shop scheduling problem with fuzzy delivery times is proposed. First, the initial population is divided into several sub-populations, and each sub-population is isolated and evolved. Next, these offspring are further optimized by a strategy that combines NEH heuristic algorithm proposed by M. Navaz, J.-E. Enscore, I. Ham in 1983 with a newly designed algorithm that has excellent local search capability, thereby enhancing the strategy’s local search capability. Then, the concept of a chaotic migration sequence is introduced to guide the ergodic process of the migration of individuals effectively so that information is exchanged sufficiently among sub-populations and the process of falling into a local optimal solution is thereby avoided. Finally, several digital simulations are provided to demonstrate the effectiveness of the algorithm proposed in this paper.

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Cite this article as:
Wen-Zhan Dai and Kai Xia, “Hybrid Genetic Algorithm Based on Chaotic Migration Strategy for Solving Flow Shop Scheduling Problem with Fuzzy Delivery Time,” J. Adv. Comput. Intell. Intell. Inform., Vol.19, No.3, pp. 359-364, 2015
Wen-Zhan Dai and Kai Xia, J. Adv. Comput. Intell. Intell. Inform., Vol.19, No.3, pp. 359-364, 2015

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