Resolution of simple plant location problems using an adapted genetic algorithm

Jorng Tzong Horng; Li Yi Lin; Baw Jhiune Liu; Cheng Yan Kao

doi:10.1109/CEC.1999.782570

Resolution of simple plant location problems using an adapted genetic algorithm

Jorng Tzong Horng, Li Yi Lin, Baw Jhiune Liu, Cheng Yan Kao

資訊工程學系

研究成果: 會議貢獻類型 › 會議論文 › 同行評審

2 引文斯高帕斯（Scopus）

摘要

This investigation presents an adapted genetic algorithm to resolve simple plant location problems. The proposed algorithm applies a clustering technique as mutation guidance and a novel local search method to enhance the solution quality. The proposed algorithm is then applied to the fifteen test problems taken from Beasley's OR-Library (J.E. Beasley, 1990). Empirical results indicate that the error rate of the proposed adapted GA is less than 0.3 percent. In addition, the computational time is bounded by a polynomial function of the problem size.

原文	???core.languages.en_GB???
頁面	1186-1193
頁數	8
DOIs	https://doi.org/10.1109/CEC.1999.782570
出版狀態	已出版 - 1999
事件	1999 Congress on Evolutionary Computation, CEC 1999 - Washington, DC, United States 持續時間: 6 7月 1999 → 9 7月 1999

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	1999 Congress on Evolutionary Computation, CEC 1999
國家/地區	United States
城市	Washington, DC
期間	6/07/99 → 9/07/99

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10.1109/CEC.1999.782570

引用此

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author = "Horng, {Jorng Tzong} and Lin, {Li Yi} and Liu, {Baw Jhiune} and Kao, {Cheng Yan}",

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AU - Horng, Jorng Tzong

AU - Lin, Li Yi

AU - Liu, Baw Jhiune

AU - Kao, Cheng Yan

PY - 1999

Y1 - 1999

N2 - This investigation presents an adapted genetic algorithm to resolve simple plant location problems. The proposed algorithm applies a clustering technique as mutation guidance and a novel local search method to enhance the solution quality. The proposed algorithm is then applied to the fifteen test problems taken from Beasley's OR-Library (J.E. Beasley, 1990). Empirical results indicate that the error rate of the proposed adapted GA is less than 0.3 percent. In addition, the computational time is bounded by a polynomial function of the problem size.

AB - This investigation presents an adapted genetic algorithm to resolve simple plant location problems. The proposed algorithm applies a clustering technique as mutation guidance and a novel local search method to enhance the solution quality. The proposed algorithm is then applied to the fifteen test problems taken from Beasley's OR-Library (J.E. Beasley, 1990). Empirical results indicate that the error rate of the proposed adapted GA is less than 0.3 percent. In addition, the computational time is bounded by a polynomial function of the problem size.

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DO - 10.1109/CEC.1999.782570

M3 - 會議論文

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T2 - 1999 Congress on Evolutionary Computation, CEC 1999

Y2 - 6 July 1999 through 9 July 1999

ER -

Resolution of simple plant location problems using an adapted genetic algorithm

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???event.eventtypes.event.conference???

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