Integrating scheduling with optimal sublot for parallel machine with job splitting and dependent setup times

被引:8
|
作者
Sethanan, Kanchana [1 ]
Wisittipanich, Warisa [2 ,3 ]
Wisittipanit, Nuttachat [4 ]
Nitisiri, Krisanarac [1 ]
Moonsri, Karn [1 ]
机构
[1] Khon Kaen Univ, Dept Ind Engn, Res Unit Syst Modeling Ind, Fac Engn, 123 Moo 16,Mittapap Rd, Khon Kaen 40002, Thailand
[2] Chiang Mai Univ, Dept Ind Engn, Fac Engn, 239 Huay Keaw Rd, Chiang Mai 50200, Thailand
[3] Chiang Mai Univ, Excellence Ctr Logist & Supply Chain Management, 239 Huay Keaw Rd, Chiang Mai 50200, Thailand
[4] Mae Fah Luang Univ, Sch Sci, Dept Mat Engn, 333 Moo 1, Muang 57100, Chiang Rai, Thailand
关键词
Parallel machine; Job splitting; Differential evolution; Particle swarm optimization; Powdered fruit beverage industry; DIFFERENTIAL EVOLUTION; OPTIMIZATION; ALGORITHM; MAKESPAN; MINIMIZE; SHOP;
D O I
10.1016/j.cie.2019.106095
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper addresses a novel problem of the parallel capacitated machines with job splitting and dependent setup times (PCMS), Pmc vertical bar split, pj, sjp vertical bar Cmax. A mixed integer programming (MIP) model is developed to find an optimal schedule with minimum makespan. Since the problem is NP-hard, metaheuristics are required to find a near optimal solution for larger, more practical problems. Therefore, this paper presents the first applications of two effective metaheuristics, Particle Swarm Optimization (PSO) and Differential Evolution (DE) with a solution representation scheme for solving the problem. To evaluate the metaheuristics' performances, the lower bound is also firstly developed. Experimental results reveal that, in the small-size problems, there are no distinctive differences between the two algorithms' performances, since both algorithms are able to find the optimal solutions. However, for medium to large size problems, the DE outperforms the PSO by providing significantly superior results of makespan for 22 out of 27 instances.
引用
收藏
页数:9
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