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

Abstract:

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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 et al., "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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Price:

$35.00

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