IMPLEMENTING A NEW GENETIC ALGORITHM TO SOLVE THE CAPACITY ALLOCATION PROBLEM IN THE PHOTOLITHOGRAPHY AREA

被引：0

作者：

Ghasemi, Amir ^{[1
]}

Heavey, Cathal ^{[1
]}

Kabak, Kamil Erkan ^{[2
]}

机构：

[1] Univ Limerick, Enterprise Res Ctr, Limerick V94 T9PX, Ireland

[2] Izmir Univ Econ, Dept Ind Engn, Sakarya Caddesi 156, TR-35330 Izmir, Turkey

来源：

2018 WINTER SIMULATION CONFERENCE (WSC) | 2018年

关键词：

CONSTRAINTS; MODEL;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：3696 / 3707

页数：12

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