Evolutional Algorithm in Solving Flexible Job Shop Scheduling Problem with Uncertainties

被引:2
|
作者
Zheng, Yahong [1 ]
Lian, Lian [2 ]
Fu, Zaifeng [2 ]
Mesghouni, Khaled [3 ]
机构
[1] Wuhan Univ Technol, Sch Transport, Wuhan 430063, Peoples R China
[2] Dalian Univ Technol, Sch Transportat & Logist, Dalian 116024, Peoples R China
[3] Ecole Cent Lille, UMR CNRS 8219, LAGIS, F-59651 Villeneuve Dascq, France
来源
LISS 2013 | 2015年
关键词
Condition based maintenance; Flexible job shop scheduling problem; Genetic algorithm; Ant colony optimization; Artificial bee algorithm;
D O I
10.1007/978-3-642-40660-7_151
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In recent years, the necessity of considering uncertainty in scheduling problem is recognized by many scholars and practitioners, but there are still not effective methods to deal with uncertainty. This paper focuses on the flexible job shop scheduling problem (FJSP). Uncertainties in FJSP includes many aspects, such as the urgently arrival jobs, the uncertain working condition of the machines, etc. In this paper, we propose an inserting algorithm (IA), which can be used to treat the necessary machine maintenance for reducing unavailability of machines. We use the condition based maintenance (CBM) to reduce unavailability of machines. A problem focused in this paper is the flexible job shop scheduling problem with preventive maintenance (FJSPPM). An inserting algorithm (IA) is utilized to add PM into a preschedule scheme of FJSP which is obtained through an evolutional algorithm. Furthermore, a new better solution for an instance in benchmark of FJSP is obtained.
引用
收藏
页码:1009 / 1015
页数:7
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