Minimization of the total weighted tardiness on a single machine scheduling problem with a position based learning effect and unequal release dates

IF 1.1 4区计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

Infor Pub Date : 2021-04-02 DOI:10.1080/03155986.2021.1904538

Settar Mustu, T. Eren

引用次数: 2

Abstract

Abstract This paper concerns with the total weighted tardiness on a single machine scheduling problem with the concept of learning effect and unequal release dates. A mathematical model is proposed with binary variables and only small size problems can be solved efficiently due to its NP-hardness. Therefore, four heuristic methods are developed to solve real size applications including the size of 1000 jobs. Proposed heuristics are: genetic, genetic with solution combination, kangaroo and genetic-kangaroo hybrid algorithms. Results denote that developed heuristics are efficient for the considered problem. Research on this topic shows that no study exists on the total weighted tardiness problem with learning effect and unequal release dates simultaneously tackled in this paper.

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基于位置学习效应和不相等放行日期的单机调度问题中总加权延迟的最小化

摘要:考虑学习效应和不相等放行日期的概念，研究单机调度问题的总加权延迟问题。提出了一种具有二元变量的数学模型，由于其np -硬度，只有小尺寸问题才能有效求解。因此，开发了四种启发式方法来解决实际规模的应用，包括1000个作业的规模。提出的启发式算法有:遗传算法、遗传带解组合算法、袋鼠算法和遗传-袋鼠混合算法。结果表明，开发的启发式方法对所考虑的问题是有效的。本课题的研究表明，目前还没有研究同时解决具有学习效应和不相等发布日期的总加权延迟问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Infor 管理科学-计算机：信息系统

CiteScore

2.60

自引率

7.70%

发文量

审稿时长

>12 weeks

期刊介绍： INFOR: Information Systems and Operational Research is published and sponsored by the Canadian Operational Research Society. It provides its readers with papers on a powerful combination of subjects: Information Systems and Operational Research. The importance of combining IS and OR in one journal is that both aim to expand quantitative scientific approaches to management. With this integration, the theory, methodology, and practice of OR and IS are thoroughly examined. INFOR is available in print and online.