期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 14, 期 12, 页码 5400-5409出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2018.2843441
关键词
Energy-efficient; multiobjective artificial bee colony algorithm (MOABC); real-life application; welding shop scheduling problem (WSSP)
类别
资金
- Natural Science Foundation of China [51775216, 51435009, 51711530038]
- Natural Science Foundation of Hubei Province [2018CFA078]
- China Postdoctoral Science Foundation [2017M622414]
- Program for HUST Academic Frontier Youth Team
Welding, an irreplaceable process in the modern manufacturing industry, consumes enormous amounts of energy. The schedule in a welding shop greatly impacts both its energy consumption and productivity. Thus, it is of great significance to solve the welding shop scheduling problem (WSSP) considering both energy efficiency and productivity. In this paper, to solve a real-life WSSP, a multiobjective mathematical model is proposed and an effective multiobjective artificial bee colony algorithm (MOABC) is developed. The results of a designed numerical experiment indicate that the proposed MOABC performs better than Strength Pareto Evolutionary Algorithm 2 and Nondominated Sorting Genetic Algorithm II. Finally, the proposed model and MOABC algorithm are applied to solve a real-life girder WSSP of a Chinese crane company. The results also demonstrate that the proposed method can greatly reduce energy consumption and makespan compared to other algorithms.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据