Hybrid evolutionary approaches for the single machine order acceptance and scheduling problem

被引:37
作者
Chaurasia, Sachchida Nand [1 ]
Singh, Alok [1 ]
机构
[1] Univ Hyderabad, Sch Comp & Informat Sci, Hyderabad 500046, Andhra Pradesh, India
关键词
Steady-state genetic algorithm; Estimation of distribution algorithm; Evolutionary algorithm; Guided mutation; Order acceptance and scheduling; Single machine scheduling; Sequence dependent setup time; DISTRIBUTION ALGORITHM; JOB-SELECTION; WEIGHTED TARDINESS; PROCESSING TIMES; SHOP; OPTIMIZATION; FLEXIBILITY;
D O I
10.1016/j.asoc.2016.09.051
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents two hybrid metaheuristic approaches, viz. a hybrid steady-state genetic algorithm (SSGA) and a hybrid evolutionary algorithm with guided mutation (EA/G) for order acceptance and scheduling (OAS) problem in a single machine environment where orders are supposed to have release dates and sequence dependent setup times are incurred in switching from one order to next in the schedule. OAS problem is an NP-hard problem. We have compared our approaches with the state-of-the-art approaches reported in the literature. Computational results show the effectiveness of our approaches. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:725 / 747
页数:23
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