A memetic algorithm to solve an unrelated parallel machine scheduling problem with auxiliary resources in semiconductor manufacturing

In this paper, we propose a metaheuristic for solving an original scheduling problem with auxiliary resources in a photolithography workshop of a semiconductor plant. The photolithography workshop is often a bottleneck, and improving scheduling decisions in this workshop can help to improve indicato...

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Vydáno v:Journal of scheduling Ročník 19; číslo 4; s. 367 - 376
Hlavní autoři: Bitar, Abdoul, Dauzère-Pérès, Stéphane, Yugma, Claude, Roussel, Renaud
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.08.2016
Springer Nature B.V
Springer Verlag
Témata:
Algorithms
Artificial Intelligence
Batch processing
Business and Management
Calculus of Variations and Optimal Control; Optimization
Computer Science
Criteria
Employment
Engineering Sciences
Genetic algorithms
Linear programming
Manufacturing
Micro and nanotechnologies
Microelectronics
Operations Research
Operations Research/Decision Theory
Optimization
Photolithography
Preventive maintenance
Production scheduling
Release dates
Scheduling
Semiconductors
Solution space
Studies
Supply Chain Management
Workshops
Parallel machines
Memetic algorithm
Scheduling
Auxiliary resources
Semiconductor Manufacturing
Setups
ISSN:1094-6136, 1099-1425
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Popis
Shrnutí:In this paper, we propose a metaheuristic for solving an original scheduling problem with auxiliary resources in a photolithography workshop of a semiconductor plant. The photolithography workshop is often a bottleneck, and improving scheduling decisions in this workshop can help to improve indicators of the whole plant. Two optimization criteria are separately considered: the weighted flow time (to minimize) and the number of products that are processed (to maximize). After stating the problem and giving some properties on the solution space, we show how these properties help us to efficiently solve the problem with the proposed memetic algorithm, which has been implemented and tested on large generated instances. Numerical experiments show that good solutions are obtained within a reasonable computational time.
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ISSN:1094-6136
1099-1425
DOI:10.1007/s10951-014-0397-6