Paper Title:
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.

  Info
Periodical
Advanced Materials Research (Volumes 268-270)
Edited by
Feng Xiong
Pages
476-481
DOI
10.4028/www.scientific.net/AMR.268-270.476
Citation
L. Gao, K. L. Xu, W. Zhu, N. N. Yang, "A Two-Stage Hybrid Algorithm for Flexible Job-Shop Scheduling", Advanced Materials Research, Vols. 268-270, pp. 476-481, 2011
Online since
July 2011
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