Genetic Algorithm Method Based on Knowledge for Minimizing the Number  of Tardy Jobs in Identical Parallel Machine Scheduling Problem

Liu Min; Wu Cheng; Dai Yuanshun

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Genetic Algorithm Method Based on Knowledge for Minimizing the Number of Tardy Jobs in Identical Parallel Machine Scheduling Problem

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- Genetic Algorithm Method Based on Knowledge for Minimizing the Number of Tardy Jobs in Identical Parallel Machine Scheduling Problem
- Acta Electronica Sinica Issue 9, Pages: 130-132(1999)
- 作者机构：
  
  清华大学自动化系!北京100084
- 作者简介：
- 基金信息：
- DOI：
  CLC： TH165
- Published：1999
- 稿件说明：
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[1]刘民,吴澄,戴元顺.最小化拖期任务数并行机调度问题的一种基于知识的遗传算法[J].电子学报,1999(09):130-132.

Liu Min, Wu Cheng, Dai Yuanshun. Genetic Algorithm Method Based on Knowledge for Minimizing the Number of Tardy Jobs in Identical Parallel Machine Scheduling Problem[J]. Acta Electronica Sinica, 1999, (9): 130-132.
[1]刘民,吴澄,戴元顺.最小化拖期任务数并行机调度问题的一种基于知识的遗传算法[J].电子学报,1999(09):130-132. DOI：

Liu Min, Wu Cheng, Dai Yuanshun. Genetic Algorithm Method Based on Knowledge for Minimizing the Number of Tardy Jobs in Identical Parallel Machine Scheduling Problem[J]. Acta Electronica Sinica, 1999, (9): 130-132. DOI：

摘要

本文研究了最小化拖期任务数并行机调度问题，提出了一种基于知识的遗传算法，并在问题的描述、遗传算法编码、初始种群的产生办法、交叉方法、变异方法等方面作了研究．不同规模问题的数值计算结果表明了本文提出的基于知识的遗传算法优于目前为止最好的启发式算法和普通的遗传算法，并且能适用于较大规模的并行机调度问题

Abstract

Identical parallel machine scheduling problem of minimizing the number of tardy jobs is studied

a genetic algorithm based on knowledge is proposed

and researches are made in these aspects such as problem formulation

coding

generation of initial population

crossover and mutating of genetic algorithm.Numerical computational results of different scale problem show that the genetic algorithm based on knowledge has advantage over so far best heuristic procedure and common genetic algorithm and is fit for larger scale identical parallel machine scheduling problem.

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