A hybrid heuristic for agent-based scheduling problem with an ordinal scale objective criterion

Scheduling with multiple agents and learning effects has attracted growing attention of the scheduling research community. However, scheduling research together with learning, multiple agents and release times considerations is few. This paper considers two-agent single-machine scheduling with a pos...

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Bibliographic Details
Published inJournal of information & optimization sciences Vol. 42; no. 1; pp. 109 - 134
Main Authors Chao, Yuan-Po, Cheng, Shuenn-Ren, Shih, Cheng-Hsiung, Yu, Kejian, Hsu, Peng-Hsiang, Chen, Hau, Wu, Wen-Hsiang
Format Journal Article
LanguageEnglish
Published Taylor & Francis 02.01.2021
Subjects
Due dates
Learning effect
Primary: 90B35
Release dates
Scheduling
Secondary: 90C26
Two-agents
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ISSN0252-2667
2169-0103
DOI10.1080/02522667.2020.1715574

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Summary:Scheduling with multiple agents and learning effects has attracted growing attention of the scheduling research community. However, scheduling research together with learning, multiple agents and release times considerations is few. This paper considers two-agent single-machine scheduling with a position-based learning effect. The criterion measurement is to minimize the number of the tardy jobs of the first agent subject to the condition that the second agent has no tardy job. A branch-and-bound and a hybrid heuristic are proposed to solve the problem.
ISSN:0252-2667
2169-0103
DOI:10.1080/02522667.2020.1715574