A Two-Stage Hybrid Algorithm for Flexible Job-Shop Scheduling

Abstract:

A mathematical model was constructed with two objectives. A two-stage hybrid algorithm was developed for solving this problem. At first, the man-hour optimization based on genetic algorithm and dynamic programming method, the model decomposes the flow shop into two layers: sub-layer and patrilineal layer. On the basis of the man-hour optimization，A simulated annealing genetic algorithm was proposed to optimize the sequence of operations. A new selection procedure was proposed and hybrid crossover operators and mutation operators were adopted. A benchmark problem solving result indicates that the proposed algorithm is effective.

• Periodical: Advanced Materials Research (Volumes 268-270)
• Pages: 476-481
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.268-270.476
• Online since: July 2011
• Authors: Li Gao, Ke Lin Xu, Wei Zhu, Na Na Yang
• Keywords: Flexible Job-Shop Scheduling, Hybrid Algorithm, Man-Hour Optimization, Multi-Objective Optimization (MOP), Sequence Operation

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