Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/36614
標題: A genetic local search algorithm for minimizing total flowtime in the permutation flowshop scheduling problem
作者: Tseng, L.Y.
曾怜玉
Lin, Y.T.
關鍵字: Genetic algorithm
Tabu search
Flowshop scheduling
Total flowtime
Genetic local search
ant-colony algorithms
sequencing problem
c-i
optimization
minimization
heuristics
jobs
期刊/報告no:: International Journal of Production Economics, Volume 127, Issue 1, Page(s) 121-128.
摘要: Recently, the flowshop scheduling problem to minimize total flowtime has attracted more attention from researchers. In this paper, a genetic local search algorithm is proposed to solve this problem. The proposed algorithm hybridizes the genetic algorithm and the tabu search. It employs the genetic algorithm to do the global search and the tabu search to do the local search. The orthogonal-array-based crossover is utilized to enhance the capability of intensification. Also, a novel orthogonal-array-based mutation is proposed, in order to add capability of intensification to the traditional mutation operator. The performance of the proposed genetic local search algorithm is very competitive. It improved 54 out of 90 current best solutions reported in the literature for short-term search, and it also improved 18 out of 20 current best solutions reported in the literature for long-term search. (C) 2010 Elsevier B.V. All rights reserved.
URI: http://hdl.handle.net/11455/36614
ISSN: 0925-5273
文章連結: http://dx.doi.org/10.1016/j.ijpe.2010.05.003
Appears in Collections:資訊網路與多媒體研究所

文件中的檔案:

取得全文請前往華藝線上圖書館



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.