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ID 20748
本文ファイル
著者
Perkgoz, Cahit
Azaron, Amir
Kato, Kosuke
キーワード
Queueing
Genetic algorithms
Multiple objective programming
Production
NDC
生物科学・一般生物学
抄録(英)
In this paper, we develop a multi-objective model to optimally control the lead time of a multistage assembly system, using genetic algorithms. The multistage assembly system is modelled as an open queueing network. It is assumed that the product order arrives according to a Poisson process. In each service station, there is either one or infinite number of servers (machines) with exponentially distributed processing time, in which the service rate (capacity) is controllable. The optimal service control is decided at the beginning of the time horizon. The transport times between the service stations are independent random variables with generalized Erlang distributions. The problem is formulated as a multi-objective optimal control problem that involves four conflicting objective functions. The objective functions are the total operating costs of the system per period (to be minimized), the average lead time (min), the variance of the lead time (min) and the probability that the manufacturing lead time does not exceed a certain threshold (max). Finally, we apply a genetic algorithm with double strings using continuous relaxation based on reference solution updating (GADSCRRSU) to solve this multi-objective problem, using goal attainment formulation. The results are also compared against the results of a discrete-time approximation technique to show the efficiency of the proposed genetic algorithm approach.
掲載誌名
European Journal of Operational Research
180巻
1号
開始ページ
292
終了ページ
308
出版年月日
2007-07-01
出版者
Elsevier Science B.V.
ISSN
0377-2217
NCID
出版者DOI
言語
英語
NII資源タイプ
学術雑誌論文
広大資料タイプ
学術雑誌論文
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
author
権利情報
Copyright (c) 2006 Elsevier B.V.
関連情報URL
部局名
工学研究科



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