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

Amir Ghasemi; Cathal Heavey; Kamil Erkan Kabak

doi:10.1109/WSC.2018.8632204

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

Amir Ghasemi
, Cathal Heavey
, Kamil Erkan Kabak

School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	WSC 2018 - 2018 Winter Simulation Conference
Subtitle of host publication	Simulation for a Noble Cause
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3696-3707
Number of pages	12
ISBN (Electronic)	9781538665725
DOIs	https://doi.org/10.1109/WSC.2018.8632204
Publication status	Published - 2 Jul 2018
Event	2018 Winter Simulation Conference, WSC 2018 - Gothenburg, Sweden Duration: 9 Dec 2018 → 12 Dec 2018

Publication series

Name	Proceedings - Winter Simulation Conference
Volume	2018-December
ISSN (Print)	0891-7736

Conference

Conference	2018 Winter Simulation Conference, WSC 2018
Country/Territory	Sweden
City	Gothenburg
Period	9/12/18 → 12/12/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

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10.1109/WSC.2018.8632204

Cite this

Ghasemi, A., Heavey, C., & Kabak, K. E. (2018). Implementing a new genetic algorithm to solve the capacity allocation problem in the photolithography area. In WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause (pp. 3696-3707). Article 8632204 (Proceedings - Winter Simulation Conference; Vol. 2018-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2018.8632204

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title = "Implementing a new genetic algorithm to solve the capacity allocation problem in the photolithography area",

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.",

author = "Amir Ghasemi and Cathal Heavey and Kabak, \{Kamil Erkan\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE; 2018 Winter Simulation Conference, WSC 2018 ; Conference date: 09-12-2018 Through 12-12-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/WSC.2018.8632204",

language = "English",

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Ghasemi, A, Heavey, C & Kabak, KE 2018, Implementing a new genetic algorithm to solve the capacity allocation problem in the photolithography area. in WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause., 8632204, Proceedings - Winter Simulation Conference, vol. 2018-December, Institute of Electrical and Electronics Engineers Inc., pp. 3696-3707, 2018 Winter Simulation Conference, WSC 2018, Gothenburg, Sweden, 9/12/18. https://doi.org/10.1109/WSC.2018.8632204

Implementing a new genetic algorithm to solve the capacity allocation problem in the photolithography area. / Ghasemi, Amir; Heavey, Cathal; Kabak, Kamil Erkan.
WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause. Institute of Electrical and Electronics Engineers Inc., 2018. p. 3696-3707 8632204 (Proceedings - Winter Simulation Conference; Vol. 2018-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Kabak, Kamil Erkan

PY - 2018/7/2

Y1 - 2018/7/2

N2 - 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.

AB - 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.

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 Winter Simulation Conference, WSC 2018

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Ghasemi A, Heavey C, Kabak KE. Implementing a new genetic algorithm to solve the capacity allocation problem in the photolithography area. In WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause. Institute of Electrical and Electronics Engineers Inc. 2018. p. 3696-3707. 8632204. (Proceedings - Winter Simulation Conference). doi: 10.1109/WSC.2018.8632204

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

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