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考虑能耗与工时恶化作用下的并行机调度优化

薛聪^1,2, 郭鹏^1,2, 陈宓^1,2, 王丽敏^1,2

(1.西南交通大学机械工程学院, 成都 610031;2.轨道交通运维技术与装备四川省重点实验室, 成都 610031)

Parallel Machine Scheduling with Step-Deteriorating Jobs and Energy Consumption

XUE Cong^1,2, GUO Peng^1,2, CHEN Mi^1,2, WANG Li-Min^1,2

(1.School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China;2.Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China)

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本文已被：浏览 1021次下载 2139次
Received:December 05, 2019 Revised:January 03, 2020

中文摘要: 在热处理加工环境中，工件温度随着其开工时刻的延误不断下降，为了能够正常加工不得不保温或重新加热.针对这一现象，本文考虑了能耗与工时恶化作用下的并行机调度问题，以最小化总拖期和能耗为目标构建了混合整数规划模型.由于问题的复杂性，提出了一种遗传变搜索算法，其通过遗传操作获得变邻域搜索操作的解集，而后使用变邻域结构进行寻优操作.算例测试表明：较之传统遗传算法以及数学规划器Gurobi的计算结果，所提出的算法可以有效减少综合能耗和拖期成本.

中文关键词: 能源消耗并行机调度工时恶化遗传算法邻域搜索

Abstract:Jobs’ temperature will decrease as their starting times delay in heat treating flow shop. In order to process the jobs normally, the worker has to reheat them or keep them in holding furnace. In response to this situation, this study considers a parallel machine scheduling problem with step-deteriorating jobs for minimizing the total tardiness and energy consumption. Firstly, a mixed integer programming model is proposed for the problem under study. Due to the intractability of the problem, a genetic -variable neighborhood search hybrid algorithm is designed to solve it. The algorithm use genetic operations to generate the solution, and then use the variable neighborhood search to improve the solution. The numerical tests show the proposed algorithm can efficiently reduce the total tardiness and energy consumption compared with standard genetic algorithm and mathematical model with standard solver Gurobi.

keywords: energy consumption parallel machine scheduling deteriorating job genetic algorithm variable neighborhood search

文章编号： 中图分类号： 文献标志码：

基金项目:国家自然科学基金（51405403）；中央高校基本科研业务费专项资金（2682018CX09）

Author Name	Affiliation	E-mail
XUE Cong	School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China
GUO Peng	School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China	pengguo318@swjtu.edu.cn
CHEN Mi	School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China
WANG Li-Min	School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China

Author Name	Affiliation	E-mail
XUE Cong	School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China
GUO Peng	School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China	pengguo318@swjtu.edu.cn
CHEN Mi	School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China
WANG Li-Min	School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610031, China

引用文本：
薛聪,郭鹏,陈宓,王丽敏.考虑能耗与工时恶化作用下的并行机调度优化.计算机系统应用,2020,29(9):66-74
XUE Cong,GUO Peng,CHEN Mi,WANG Li-Min.Parallel Machine Scheduling with Step-Deteriorating Jobs and Energy Consumption.COMPUTER SYSTEMS APPLICATIONS,2020,29(9):66-74