期刊
JOURNAL OF CLEANER PRODUCTION
卷 137, 期 -, 页码 1516-1531出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2016.07.029
关键词
Multi-objective evolutionary algorithm; Energy consumption; Parameter optimization; Backtracking search algorithm
资金
- National Science Foundation of China (NSFC) [51435009, 51375004]
- postdoctoral Science Foundation of China [2015T80798]
- Youth Science & Technology Chenguang Program of Wuhan [2015070404010187]
- Fundamental Research Funds for the Central Universities, HUST [2015TS061]
Energy savings have become an essential consideration in sustainable manufacturing projects due to the associated environmental impacts and constraints on carbon emissions. In the past, machining operations primarily examined technological consideration (e.g., machining quality) and neglected energy consumption. Therefore, this paper investigates an energy-efficient multi-pass turning operation problem and establishes a multi-objective multi-pass turning operations model. Energy consumption and machining quality are both considered in this problem. Although several models of this problem have considered these criteria, the objectives are usually combined into a single objective using a weighted sum approach, which results in poor non-dominated solutions. To obtain high quality trade-offs between the two challenging objectives, a novel multi-objective backtracking search algorithm is proposed to solve this multi-objective optimization problem. To verify the feasibility and validity of the proposed algorithm, it is compared with other classical multi-objective metaheuristics on multi-objective multi pass turning operations. This study's experimental results demonstrate that the proposed algorithm significantly outperforms other algorithms for this optimization problem, which is a significant result regarding practical application. (C) 2016 Elsevier Ltd. All rights reserved.
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