A genetic algorithm and a simulated annealing algorithm combined with column generation technique for solving the problem of scheduling in the hybrid flowshop with additional resources-Reference-Cited by-同舟云学术

A genetic algorithm and a simulated annealing algorithm combined with column generation technique for solving the problem of scheduling in the hybrid flowshop with additional resources

Published:2009-02 Issue:1 Volume:56 Page:142-151
ISSN:0360-8352
Container-title:Computers & Industrial Engineering
language:en
Short-container-title:Computers & Industrial Engineering

Author:

Figielska Ewa

Publisher

Elsevier BV

Subject

General Engineering,General Computer Science

Reference36 articles.

1. Aarts, E. H. L., & van Laarhoven, P. J. M. (1987), Simulated annealing: Theory and applications. Reidel, Dordrecht.

2. A scheduling support system for the packaging industry;Adler;Operations Research,1993

3. Branch and price: Column generation for solving huge integer problems;Barnhart;Operations Research,1998

4. Błażewicz, J., Cellary, W., Słowiński, R., & Węglarz, J. (1987). Scheduling under resource constraints: Deterministic models. Basel: J.C. Baltzer.

5. Heuristics for scheduling in a flow shop with multiple processors;Brah;European Journal of Operational Research,1999

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