No-Wait Flowshops to Minimize Total Tardiness with Setup Times  

作　　者：Tariq Aldowaisan Ali Allahverdi 

机构地区：[1]Department of Industrial and Management Systems Engineering, Kuwait University, Kuwait City, Kuwait

出　　处：《Intelligent Control and Automation》2015年第1期38-44,共7页智能控制与自动化（英文）

摘　　要：The m-machine no-wait flowshop scheduling problem is addressed where setup times are treated as separate from processing times. The objective is to minimize total tardiness. Different dispatching rules have been investigated and three were found to be superior. Two heuristics, a simulated annealing (SA) and a genetic algorithm (GA), have been proposed by using the best performing dispatching rule as the initial solution for SA, and the three superior dispatching rules as part of the initial population for GA. Moreover, improved versions of SA and GA are proposed using an insertion algorithm. Extensive computational experiments reveal that the improved versions of SA and GA perform about 95% better than SA and GA. The improved version of GA outperforms the improved version of SA by about 3.5%.The m-machine no-wait flowshop scheduling problem is addressed where setup times are treated as separate from processing times. The objective is to minimize total tardiness. Different dispatching rules have been investigated and three were found to be superior. Two heuristics, a simulated annealing (SA) and a genetic algorithm (GA), have been proposed by using the best performing dispatching rule as the initial solution for SA, and the three superior dispatching rules as part of the initial population for GA. Moreover, improved versions of SA and GA are proposed using an insertion algorithm. Extensive computational experiments reveal that the improved versions of SA and GA perform about 95% better than SA and GA. The improved version of GA outperforms the improved version of SA by about 3.5%.

关 键 词：NO-WAIT FLOWSHOP Scheduling SETUP TIMES Total TARDINESS Simulated Annealing GENETIC Algorithm 

分 类 号：R73[医药卫生—肿瘤]