A hybrid genetic algorithm with dominance properties for single machine scheduling with dependent penalties

doi:10.1016%2Fj.apm.2008.01.006

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題名:	A hybrid genetic algorithm with dominance properties for single machine scheduling with dependent penalties
作者:	Chang, Pei Chann;Chen, Shih Hsin;Mani, V.
關鍵詞:	Single machine scheduling;Earliness/tardiness;Dominance properties;Genetic algorithm;Optimal schedule
日期:	2009
上傳時間:	2021-10-07 12:10:44 (UTC+8)
出版者:	Elsevier Inc.
摘要:	In this paper, a hybrid genetic algorithm is developed to solve the single machine scheduling problem with the objective to minimize the weighted sum of earliness and tardiness costs. First, dominance properties of (the conditions on) the optimal schedule are developed based on the switching of two adjacent jobs i and j. These dominance properties are only necessary conditions and not sufficient conditions for any given schedule to be optimal. Therefore, these dominance properties are further embedded in the genetic algorithm and we call it genetic algorithm with dominance properties (GADP). This GADP is a hybrid genetic algorithm. The initial populations of schedules in the genetic algorithm are generated using these dominance properties. GA can further improve the performance of these initial solutions after the evolving procedures. The performances of hybrid genetic algorithm (GADP) have been compared with simple genetic algorithm (SGA) using benchmark instances. It is shown that this hybrid genetic algorithm (GADP) performs very well when compared with DP or SGA alone.
關聯:	Applied Mathematical Modelling 33(1), p.579-596
DOI:	10.1016%2Fj.apm.2008.01.006
顯示於類別:	[資訊工程學系暨研究所] 期刊論文

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