Multi-objective stochastic scheduling of job ready times

被引:0
|
作者
Paul M. Stanfield
Russell E. King
Thom J. Hodgson
机构
来源
Annals of Operations Research | 1997年 / 70卷
关键词
Genetic Algorithm; Service Time; Ready Time; Stochastic Schedule; Minimum Acceptable Level;
D O I
暂无
中图分类号
学科分类号
摘要
A fundamental scheduling problem is to determine a production start (ready) time based on customer-specified due dates. Typically, the objective is to delay the ready time in an attempt to minimize work-in-process inventory and maximize production system utilization. In many practical situations, highly variable service times complicate this problem. In such a case, the ready time implies a level of on-time completion confidence for each job. As the ready time increases, the on-time confidence decreases. This paper investigates the ready time/job confidence level tradeoff. A multi-objective model balances the ready time and confidence level maximization goals. The model involves combinatorial and numerical optimization and has an exceptionally complex state space. In view of these complexities, we investigate a pairwise interchange heuristic and a genetic algorithm search solution. Experimental results support solution through a process involving both the heuristic and the genetic algorithm.
引用
收藏
页码:221 / 239
页数:18
相关论文
共 50 条
  • [1] Multi-objective stochastic scheduling of job ready times
    Stanfield, PM
    King, RE
    Hodgson, TJ
    ANNALS OF OPERATIONS RESEARCH, 1997, 70 (0) : 221 - 239
  • [2] Simplified multi-objective genetic algorithms for stochastic job shop scheduling
    Lei, Deming
    APPLIED SOFT COMPUTING, 2011, 11 (08) : 4991 - 4996
  • [3] An efficient evolutionary algorithm for multi-objective stochastic job shop scheduling
    Lei, De-Ming
    Xiong, He-Jin
    PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 867 - 872
  • [4] A New Hybrid Multi-objective Pareto Archive PSO Algorithm for a Classic Job Shop Scheduling Problem with Ready Times
    Tavakkoli-Moghaddam, Reza
    Azarkish, Mojgan
    Sadeghnejad, Azar
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, 2010, 93 : 61 - 68
  • [5] Robustness measures and robust scheduling for multi-objective stochastic flexible job shop scheduling problems
    Xiao-Ning Shen
    Ying Han
    Jing-Zhi Fu
    Soft Computing, 2017, 21 : 6531 - 6554
  • [6] Robustness measures and robust scheduling for multi-objective stochastic flexible job shop scheduling problems
    Shen, Xiao-Ning
    Han, Ying
    Fu, Jing-Zhi
    SOFT COMPUTING, 2017, 21 (21) : 6531 - 6554
  • [7] Multi-objective enhanced memetic algorithm for green job shop scheduling with uncertain times
    Afsar, Sezin
    Jose Palacios, Juan
    Puente, Jorge
    Vela, Camino R.
    Gonzalez-Rodriguez, Ines
    SWARM AND EVOLUTIONARY COMPUTATION, 2022, 68
  • [8] Research on multi-objective fuzzy job shop scheduling
    Lei, De-Ming
    Wu, Zhi-Ming
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2006, 12 (02): : 174 - 179
  • [9] Study on Job Shop Scheduling Optimization with Multi-objective
    Ze, Tao
    Di, Liang
    Qun, Zhou
    HIGH PERFORMANCE STRUCTURES AND MATERIALS ENGINEERING, PTS 1 AND 2, 2011, 217-218 : 326 - +
  • [10] Approach for Multi-objective Flexible Job shop scheduling
    Hui, Hongjie
    AUTOMATIC MANUFACTURING SYSTEMS II, PTS 1 AND 2, 2012, 542-543 : 407 - 410