王延章

个人信息Personal Information

教授

博士生导师

硕士生导师

任职 : 电子政务模拟仿真国家地方联合工程研究中心主任

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:信息与决策技术研究所

电子邮箱:yzwang@dlut.edu.cn

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Integrated rescheduling and preventive maintenance for arrival of new jobs through evolutionary multi-objective optimization

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论文类型:期刊论文

发表时间:2016-04-01

发表刊物:SOFT COMPUTING

收录刊物:SCIE、EI

卷号:20

期号:4

页面范围:1635-1652

ISSN号:1432-7643

关键字:Rescheduling; Multi-objective optimization; Pareto optimality; Preventive maintenance; Deteriorating

摘要:In this paper, we study a rescheduling problem in response to arrival of new jobs in single machine layout, where preventive maintenance should be determined. Preventive maintenance together with controllable processing time could alleviate the inherent deteriorating effect in manufacturing system. Processing sequence of original and new jobs, compression of each job, and position of maintenance should be optimized simultaneously with regards to total operational cost (job's total completion times, maintenance cost and compression cost) and total completion time deviation. An improved elitist non-dominated sorting genetic algorithm (NSGA-II) has been proposed to solve the rescheduling problem. To address the key problem of balancing between exploration and exploitation, we hybridize differential evolution mutation operation with NSGA-II to enhance diversity, constitute high-quality initial solution based on assignment model for exploitation, and incorporate analytic property of non-dominated solutions for exploration. Finally computational study is designed by randomly generating various instances with regards to the problem size from given distributions. By use of existing performance indicators for convergence and diversity of Pareto fronts, we illustrate the effectiveness of the hybrid algorithm and the incorporation of domain knowledge into evolutionary optimization in rescheduling.