Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/3659
Title: | Implementing a New Genetic Algorithm To Solve the Capacity Allocation Problem in the Photolithography Area | Authors: | Ghasemi A. Heavey C. Kabak K.E. |
Keywords: | Efficiency Genetic algorithms Photolithography Capacity allocation Effectiveness and efficiencies Machine dedication New genetic algorithms Real case Reference group Semiconductor manufacturing Semiconductor manufacturing systems Semiconductor device manufacture |
Publisher: | Institute of Electrical and Electronics Engineers Inc. | 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. © 2018 IEEE | Description: | Arena;Bayer;Chalmers;et al.;Simio;The AnyLogic Company 2018 Winter Simulation Conference, WSC 2018 -- 9 December 2018 through 12 December 2018 -- 144832 |
URI: | https://doi.org/10.1109/WSC.2018.8632204 https://hdl.handle.net/20.500.14365/3659 |
ISBN: | 9.78E+12 | ISSN: | 0891-7736 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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