Implementing a new genetic algorithm to solve the capacity allocation problem in the photolithography area

Amir Ghasemi, Cathal Heavey, Kamil Erkan Kabak

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Photolithography plays a key role in semiconductor manufacturing systems. In this paper, we address the capacity allocation problem in the photolithography area (CAPPA) subject to machine dedication and tool capability constraints. After proposing the mathematical model of the considered problem, we present a new genetic algorithm named RGA which was derived from a psychological concept called Reference Group in society. Finally, to evaluate the efficiency of the algorithm, we solve a real case study problem from a semiconductor manufacturing company in Ireland and compare the results with one of the genetic algorithms proposed in the literature. Results show the effectiveness and efficiency of RGA to solve CAPPA in a reasonable time.

Original languageEnglish
Title of host publicationWSC 2018 - 2018 Winter Simulation Conference
Subtitle of host publicationSimulation for a Noble Cause
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3696-3707
Number of pages12
ISBN (Electronic)9781538665725
DOIs
Publication statusPublished - 2 Jul 2018
Event2018 Winter Simulation Conference, WSC 2018 - Gothenburg, Sweden
Duration: 9 Dec 201812 Dec 2018

Publication series

NameProceedings - Winter Simulation Conference
Volume2018-December
ISSN (Print)0891-7736

Conference

Conference2018 Winter Simulation Conference, WSC 2018
Country/TerritorySweden
CityGothenburg
Period9/12/1812/12/18

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