An Estimation of Distribution Algorithm Based on Copula for Parallel Machine Scheduling with Constrained Waiting Time

CAO Zheng-cai; LIN Cheng-ran; HUANG Ran

doi:10.3969/j.issn.0372-2112.2017.12.017

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An Estimation of Distribution Algorithm Based on Copula for Parallel Machine Scheduling with Constrained Waiting Time

更新时间：2025-07-16

- An Estimation of Distribution Algorithm Based on Copula for Parallel Machine Scheduling with Constrained Waiting Time
- Acta Electronica Sinica Vol. 45, Issue 12, Pages: 2949-2956(2017)
- 作者机构：
  
  北京化工大学信息科学与技术学院,北京,100029
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2017.12.017
  CLC： TP273
- Published Online：25 December 2017，
  
  Published：2017
- 稿件说明：
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CAO Zheng-cai, LIN Cheng-ran, HUANG Ran. An Estimation of Distribution Algorithm Based on Copula for Parallel Machine Scheduling with Constrained Waiting Time[J]. Acta Electronica Sinica, 2017, 45(12): 2949-2956.
DOI：

CAO Zheng-cai, LIN Cheng-ran, HUANG Ran. An Estimation of Distribution Algorithm Based on Copula for Parallel Machine Scheduling with Constrained Waiting Time[J]. Acta Electronica Sinica, 2017, 45(12): 2949-2956. DOI： 10.3969/j.issn.0372-2112.2017.12.017.

摘要

本文针对一类带等待时间约束的不相关并行机调度问题，提出了一种基于Copula函数的分布估计算法.该算法以同类订单工件数与总工件数的比值为变量，对每台机器构造了一个Copula函数，进而建立了优势种群的概率模型.基于概率模型通过采样生成子代个体编码向量组，保留了父代种群的相对位置信息.从理论上分析了所提出算法的时间复杂度，其随工件个数的增加呈对数增长.通过基于实例的数值仿真以及与已有算法的比较验证了所提算法的有效性和鲁棒性.

Abstract

This paper proposes an estimation of distribution algorithm based on Copula for solving parallel machine scheduling problem with constrained waiting time.By considering the ratios of each class of orders to total lots as variables

a Copula function is constructed for each machine

and then the probability model of the dominant population is established.This algorithm generates individual coding vector group by sampling based on the probability model

and preserves the relative location information of the parent population.The time complexity of the proposed algorithm is analyzed

which increases logarithmically as the number of lots raises.Simulation results based on some instances and comparisons with some existing algorithms demonstrate the effectiveness and robustness of the proposed algorithm.

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