Optimization Approaches for a General Class of Single-Machine Scheduling Problems

Haitao Li; Bahram Alidaee

doi:10.1007/978-3-031-62922-8_22

Optimization Approaches for a General Class of Single-Machine Scheduling Problems

Haitao Li, Bahram Alidaee

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Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Metaheuristics - 15th International Conference, MIC 2024, Proceedings
Editors	Marc Sevaux, Alexandru-Liviu Olteanu, Eduardo G. Pardo, Angelo Sifaleras, Salma Makboul
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	321-327
Number of pages	7
ISBN (Print)	9783031629211
DOIs	https://doi.org/10.1007/978-3-031-62922-8_22
State	Published - 2024
Event	15th Metaheuristics International Conference, MIC 2024 - Lorient, France Duration: Jun 4 2024 → Jun 7 2024

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14754 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th Metaheuristics International Conference, MIC 2024
Country/Territory	France
City	Lorient
Period	6/4/24 → 6/7/24

ASJC Scopus Subject Areas

Theoretical Computer Science
General Computer Science

Keywords

earliness-tardiness
mixed-integer linear programming
no idle time
setup cost
setup time
single machine scheduling
tabu search

Access to Document

10.1007/978-3-031-62922-8_22

Cite this

Li, H., & Alidaee, B. (2024). Optimization Approaches for a General Class of Single-Machine Scheduling Problems. In M. Sevaux, A.-L. Olteanu, E. G. Pardo, A. Sifaleras, & S. Makboul (Eds.), Metaheuristics - 15th International Conference, MIC 2024, Proceedings (pp. 321-327). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14754 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-62922-8_22

Optimization Approaches for a General Class of Single-Machine Scheduling Problems. / Li, Haitao; Alidaee, Bahram.
Metaheuristics - 15th International Conference, MIC 2024, Proceedings. ed. / Marc Sevaux; Alexandru-Liviu Olteanu; Eduardo G. Pardo; Angelo Sifaleras; Salma Makboul. Springer Science and Business Media Deutschland GmbH, 2024. p. 321-327 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14754 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, H & Alidaee, B 2024, Optimization Approaches for a General Class of Single-Machine Scheduling Problems. in M Sevaux, A-L Olteanu, EG Pardo, A Sifaleras & S Makboul (eds), Metaheuristics - 15th International Conference, MIC 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14754 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 321-327, 15th Metaheuristics International Conference, MIC 2024, Lorient, France, 6/4/24. https://doi.org/10.1007/978-3-031-62922-8_22

Li H, Alidaee B. Optimization Approaches for a General Class of Single-Machine Scheduling Problems. In Sevaux M, Olteanu AL, Pardo EG, Sifaleras A, Makboul S, editors, Metaheuristics - 15th International Conference, MIC 2024, Proceedings. Springer Science and Business Media Deutschland GmbH. 2024. p. 321-327. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-62922-8_22

Li, Haitao ; Alidaee, Bahram. / Optimization Approaches for a General Class of Single-Machine Scheduling Problems. Metaheuristics - 15th International Conference, MIC 2024, Proceedings. editor / Marc Sevaux ; Alexandru-Liviu Olteanu ; Eduardo G. Pardo ; Angelo Sifaleras ; Salma Makboul. Springer Science and Business Media Deutschland GmbH, 2024. pp. 321-327 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Optimization Approaches for a General Class of Single-Machine Scheduling Problems

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ASJC Scopus Subject Areas

Keywords

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