An Improved MOEA/D Algorithm for the Carbon Black Production Line Static and Dynamic Multiobjective Scheduling Problem

被引:0
|
作者
Wang, Yao [1 ]
Dong, Zhiming [2 ]
Hu, Tenghui [3 ]
Wang, Xianpeng [4 ]
机构
[1] Northeastern Univ, Minist Educ, Key Lab Data Analyt & Optimizat Smart Ind, Shenyang, Peoples R China
[2] Northeastern Univ, Liaoning Engn Lab Operat Analyt & Optimizat Smart, Shenyang, Peoples R China
[3] Northeastern Univ, Liaoning Key Lab Mfg Syst & Logist, Shenyang, Peoples R China
[4] Northeastern Univ, Inst Ind & Syst Engn, Shenyang, Peoples R China
基金
中国国家自然科学基金; 国家自然科学基金重大项目;
关键词
MTO; order static scheduling; rush order dynamic rescheduling; multiobjecfive optimization; MOEA/D;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The make-to-order (MTO) manufacturers generally make production plans based on orders, which can help enterprises effectively avoid market risks, reduce market pressure and improve competitiveness. However, due to the characteristics of MTO production mode, the order static scheduling problem and rush order dynamic rescheduling problem have become more and more important for these MTO manufacturers. Therefore, in this paper, we take the packaging production line of a typical carbon black production enterprise as the research background to study the carbon black production line static and dynamic multiobjective scheduling problem. Firstly, multiobjective optimization models of both order static scheduling and rush order dynamic rescheduling are established. Then the improved MOEA/D algorithm combined the heuristic algorithm based on heuristic rules and discrete dynamic local search is developed to solve these two models. Based on the actual production data, eight instances of order static scheduling problems of different scales and four instances of rush order dynamic rescheduling problems of different scales are constructed respectively. Experimental results illustrate that the improved MOEA/D is effective and superior in solving these two problems.
引用
收藏
页数:8
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