research-article

A Dispatching rule based Genetic Algorithm for Order Acceptance and Scheduling

Authors:

Kay Chen TanAuthors Info & Claims

GECCO '15: Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation

Pages 433 - 440

https://doi.org/10.1145/2739480.2754821

Published: 11 July 2015 Publication History

Abstract

Order acceptance and scheduling is an interesting and chal- lenging scheduling problem in which two decisions need to be handled simultaneously. While the exact methods are not efficient and sometimes impractical, existing meta-heuristics proposed in the literature still have troubles dealing with large problem instances. In this paper, a dispatching rule based genetic algorithm is proposed to combine the advan- tages of existing dispatching rules/heuristics, genetic algo- rithm and local search. The results indicates that the pro- posed methods are effective and efficient when compared to a number of existing heuristics with a wide range of problem instances.

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Cited By

Salamun KDzapo H(2024)A Cooperative Coevolutionary Approach to Designing Acceptance Tests for Jobs With Weakly Hard Real- Time Constraints2024 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC60901.2024.10612030(1-8)Online publication date: 30-Jun-2024
https://doi.org/10.1109/CEC60901.2024.10612030
Li GLi XLi JChen JShen X(2024)PTMB: An online satellite task scheduling framework based on pre-trained Markov decision process for multi-task scenarioKnowledge-Based Systems10.1016/j.knosys.2023.111339284(111339)Online publication date: Jan-2024
https://doi.org/10.1016/j.knosys.2023.111339
Laalaoui YM’Hallah R(2024)Enhancing the best-first-search F with incremental search and restarts for large-scale single machine scheduling with release dates and deadlinesAnnals of Operations Research10.1007/s10479-024-06386-7Online publication date: 21-Nov-2024
https://doi.org/10.1007/s10479-024-06386-7
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Index Terms

A Dispatching rule based Genetic Algorithm for Order Acceptance and Scheduling
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
    2. Search methodologies
2. Theory of computation
  1. Design and analysis of algorithms
    1. Algorithm design techniques
      1. Dynamic programming

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cover image ACM Conferences

GECCO '15: Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation

July 2015

1496 pages

ISBN:9781450334723

DOI:10.1145/2739480

Editor:
Sara Silva
Universidade de Lisboa, Portugal
,
General Chair:
Anna I. Esparcia-Alcázar
Universitat Politècnica de València, Spain

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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New York, NY, United States

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Published: 11 July 2015

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GECCO '15

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SIGEVO

GECCO '15: Genetic and Evolutionary Computation Conference

July 11 - 15, 2015

Madrid, Spain

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GECCO '15 Paper Acceptance Rate 182 of 505 submissions, 36%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Salamun KDzapo H(2024)A Cooperative Coevolutionary Approach to Designing Acceptance Tests for Jobs With Weakly Hard Real- Time Constraints2024 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC60901.2024.10612030(1-8)Online publication date: 30-Jun-2024
https://doi.org/10.1109/CEC60901.2024.10612030
Li GLi XLi JChen JShen X(2024)PTMB: An online satellite task scheduling framework based on pre-trained Markov decision process for multi-task scenarioKnowledge-Based Systems10.1016/j.knosys.2023.111339284(111339)Online publication date: Jan-2024
https://doi.org/10.1016/j.knosys.2023.111339
Laalaoui YM’Hallah R(2024)Enhancing the best-first-search F with incremental search and restarts for large-scale single machine scheduling with release dates and deadlinesAnnals of Operations Research10.1007/s10479-024-06386-7Online publication date: 21-Nov-2024
https://doi.org/10.1007/s10479-024-06386-7
Zeng HWang HZhang BWang Q(2023)A methodology to quantify the neighborhood decay effect of urban cellular automata modelsInternational Journal of Geographical Information Science10.1080/13658816.2023.218641237:6(1236-1263)Online publication date: 14-Mar-2023
https://doi.org/10.1080/13658816.2023.2186412
Laalaoui YM'Hallah R(2022)A problem-independent search heuristic for single machine scheduling with release dates and deadlines2022 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI51031.2022.10022172(782-789)Online publication date: 4-Dec-2022
https://doi.org/10.1109/SSCI51031.2022.10022172
Planinic LBackovic HDurasevic MJakobovic D(2022)A Comparative Study of Dispatching Rule Representations in Evolutionary Algorithms for the Dynamic Unrelated Machines EnvironmentIEEE Access10.1109/ACCESS.2022.315134610(22886-22901)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3151346
He Lde Weerdt MYorke-Smith N(2019)Time/sequence-dependent scheduling: the design and evaluation of a general purpose tabu-based adaptive large neighbourhood search algorithmJournal of Intelligent Manufacturing10.1007/s10845-019-01518-4Online publication date: 20-Dec-2019
https://doi.org/10.1007/s10845-019-01518-4
Ɖurasević MJakobović D(2019)Creating dispatching rules by simple ensemble combinationJournal of Heuristics10.1007/s10732-019-09416-xOnline publication date: 29-May-2019
https://doi.org/10.1007/s10732-019-09416-x
Sabar NTurky ASong ATakadama K(2018)A genetic programming based iterated local search for software project schedulingProceedings of the Genetic and Evolutionary Computation Conference10.1145/3205455.3205557(1364-1370)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3205455.3205557
Silva YSubramanian APessoa A(2018)Exact and heuristic algorithms for order acceptance and scheduling with sequence-dependent setup timesComputers and Operations Research10.1016/j.cor.2017.09.00690:C(142-160)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1016/j.cor.2017.09.006
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