MULTI-OBJECTIVE FLEXIBLE JOB SHOP SCHEDULING PROBLEM WITH CARBON EMISSIONS

被引：0
|
作者：
Zhang, Guo-Hui [1 ]
Dang, Shi-Jie [1 ]
Deng, Xiang [1 ]
机构：
[1] Zhengzhou Inst Aeronaut Ind Management, Sch Management Sci & Engn, Zhengzhou, Henan, Peoples R China
来源：
ENERGY AND MECHANICAL ENGINEERING | 2016年
基金：
中国国家自然科学基金;
关键词：
Flexible job shop scheduling problem; Carbon emissions; Multi-objective optimization; Pareto solution set; ALGORITHM;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
An improved genetic algorithm is proposed for solving the actual situation with preparation time and unloading time in a manufacturing job-shop, a multi-objective scheduling model is put forward, including the maximal completion time, the maximal machine workload, the total workload of the machines and the minimum of carbon emissions in the production process. According to the characteristics of multi-objective flexible job shop scheduling problem, an improved genetic algorithm is designed to improve the initial solution quality, by using effective genetic algorithm to avoid premature of the algorithm, reduce the algorithm complexity and improve the algorithm efficiency. The scheduling model with carbon emissions makes the scheduling problem more realistic, the experimental results demonstrate the feasibility of the scheduling model and the effectiveness of the algorithm.
引用
收藏
页码：946 / 952
页数：7
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