A genetic algorithm with sub-indexed partitioning genes and its application to production scheduling of parallel machines
學年 93
學期 1
出版（發表）日期 2005-01-01
作品名稱 A genetic algorithm with sub-indexed partitioning genes and its application to production scheduling of parallel machines
作品名稱（其他語言）
著者 周清江; Jou, Chi-chang
單位 淡江大學資訊管理學系
出版者 Elsevier
著錄名稱、卷期、頁數 Computers & Industrial Engineering 48(1), pp.39-54
摘要 Production scheduling seeks optimal combination of short manufacturing time, stable inventory, balanced human and machine utilization rate, and short average customer waiting time. Since the problem in general has been proven as NP-hard, we focus on suboptimal scheduling solutions for parallel flow shop machines where jobs are queued in a bottleneck stage. A Genetic Algorithm with Sub-indexed Partitioning genes (GASP) is proposed to allow more flexible job assignments to machines. Our fitness function considers tardiness, earliness, and utilization rate related variable costs to reflect real requirements. A premature convergence bounce is added to traditional genetic algorithms to increase permutation diversity. Finally, a production scheduling system for an electronic plant based on GASP is implemented and illustrated through real production data. The proposed GASP has demonstrated the following advantages: (1) the solutions from GASP are better and with smaller deviations than those from heuristic rules and genetic algorithms with identical partitioning genes; (2) the added premature convergence bounce helps obtain better solutions with smaller deviations; and (3) the consideration of variable costs in the fitness function helps achieve better performance indicators.
關鍵字 Production scheduling;Genetic algorithms;Flow shop;Parallel machines
語言 en
ISSN 0360-8352
期刊性質 國外
收錄於
產學合作
通訊作者
審稿制度 否
國別 GBR
公開徵稿
出版型式 ,紙本
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