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


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

December 15, 2013
February 2, 2015
Online released:
May 20, 2015
May 20, 2015
flow shop scheduling problem, genetic algorithm, chaotic migration, fuzzy delivery time

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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Last updated on Jun. 25, 2017