Scheduling an Energy-Aware Parallel Machine System with Deteriorating and Learning Effects Considering Multiple Optimization Objectives and Stochastic Processing Time  

作　　者：Lei Wang Yuxin Qi 

机构地区：[1]School of Event and Economic Management,Shanghai Institute of Tourism,Shanghai,201418,China [2]School of Tourism,Shanghai Normal University,Shanghai,201418,China

出　　处：《Computer Modeling in Engineering & Sciences》2023年第4期325-339,共15页工程与科学中的计算机建模（英文）

摘　　要：Currently,energy conservation draws wide attention in industrial manufacturing systems.In recent years,many studies have aimed at saving energy consumption in the process of manufacturing and scheduling is regarded as an effective approach.This paper puts forwards a multi-objective stochastic parallel machine scheduling problem with the consideration of deteriorating and learning effects.In it,the real processing time of jobs is calculated by using their processing speed and normal processing time.To describe this problem in a mathematical way,amultiobjective stochastic programming model aiming at realizing makespan and energy consumption minimization is formulated.Furthermore,we develop a multi-objective multi-verse optimization combined with a stochastic simulation method to deal with it.In this approach,the multi-verse optimization is adopted to find favorable solutions from the huge solution domain,while the stochastic simulation method is employed to assess them.By conducting comparison experiments on test problems,it can be verified that the developed approach has better performance in coping with the considered problem,compared to two classic multi-objective evolutionary algorithms.

关 键 词：Energy consumption optimization parallel machine scheduling multi-objective optimization deteriorating and learning effects stochastic simulation 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]