A new model for single machine scheduling with uncertain processing time

被引：20
|
作者：
Hu, Kai [1 ]
Zhang, Xingfang [1 ]
Gen, Mitsuo [2 ,3 ]
Jo, Jungbok [4 ]
机构：
[1] Liaocheng Univ, Sch Math Sci, Liaocheng 252059, Peoples R China
[2] Tokyo Univ Sci, Tokyo, Japan
[3] Japan & Fuzzy Log Syst Inst, Iizuka, Fukuoka, Japan
[4] Dongseo Univ, Div Comp & Informat Engn, Busan, South Korea
来源：
JOURNAL OF INTELLIGENT MANUFACTURING | 2017年 / 28卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Integer programming; Uncertainty theory; Batch scheduling; RENEWAL PROCESS; MINIMIZE; ENTROPY; BATCH; JOBS;
D O I：
10.1007/s10845-015-1033-9
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Uncertain single machine scheduling problem for batches of jobs is an important issue for manufacturing systems. In this paper, we use uncertainty theory to study the single machine scheduling problem with deadlines where the processing times are described by uncertain variables with known uncertainty distributions. A new model for this problem is built to maximize expected total weight of batches of jobs. Then the model is transformed into a deterministic integer programming model by using the operational law for inverse uncertainty distributions. In addition, a property of the transformed model is provided and an algorithm is designed to solve this problem. Finally, a numerical example is given to illustrate the effectiveness of the model and the proposed algorithm.
引用
收藏
页码：717 / 725
页数：9
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