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2013 | OriginalPaper | Chapter

15. A Modified Simulated Annealing Algorithm for Optimal Capacity Allocation in Make-to-Order Job-Shops

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Abstract

This paper presents a new capacity allocation method to support decisions in the design or redesign of a make-to-order job-shop with stochastic orders and processing times. The solutions for capacity allocation can be adding/removing machines or work shifts at every work stations. A bi-criteria objective function comprising fixed costs and tardiness penalty is used to evaluate each solution. A simulation model is applied to compute the objective function iteratively in a modified simulated annealing procedure until a feasible and profitable solution is generated. Bottleneck analysis is used as guidance for the neighborhood-generation in the modified simulated annealing procedure in order to accelerate convergence. Consequently, the run time of the procedure is short enough for practical use. Different problems were tested. Solutions from the proposed method were compared to those from the classical simulated annealing and the comparison showed relatively positive results.

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Literature
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Metadata
Title
A Modified Simulated Annealing Algorithm for Optimal Capacity Allocation in Make-to-Order Job-Shops
Author
Liang Huang
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-33012-4_15