Integer Programming Models and Metaheuristics for Customer Order Scheduling Full article
| Conference |
XXIII International Conference Mathematical Optimization Theory and Operations Research 30 Jun - 6 Jul 2024 , Омск |
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| Source | Mathematical Optimization Theory and Operations Research: Recent Trends Compilation, Springer. 2024. 388 c. ISBN 978-3-031-73364-2. |
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| Journal |
Communications in Computer and Information Science
ISSN: 1865-0929 |
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| Output data | Year: 2024, Volume: 2239, Pages: 276–290 Pages count : 14 DOI: 10.1007/978-3-031-73365-9_19 | ||
| Tags | scheduling · production · setup time · model · algorithm | ||
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| Affiliations |
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Funding (1)
| 1 | Russian Science Foundation | 22-71-10015 |
Abstract:
The problem of scheduling customer orders in a production unit is investigated. The order of a customer consists of several products. When the unit is switched from one product to another a setup operation arises. We consider two criteria: the total completion time and the weighted number of orders completed by their due dates. We provide and compare several approaches to construct integer linear programming models of the problem. A memetic algorithm with optimized operators is proposed for searching near optimal solutions. The results of the experimental evaluation are analysed on a series of instances and compared with state-of-the-art metaheuristics.
Cite:
Zakharova Y.V.
, Zakharov A.O.
Integer Programming Models and Metaheuristics for Customer Order Scheduling
In compilation Mathematical Optimization Theory and Operations Research: Recent Trends. – Springer., 2024. – Т.2239. – C.276–290. – ISBN 978-3-031-73364-2. DOI: 10.1007/978-3-031-73365-9_19 Scopus OpenAlex
Integer Programming Models and Metaheuristics for Customer Order Scheduling
In compilation Mathematical Optimization Theory and Operations Research: Recent Trends. – Springer., 2024. – Т.2239. – C.276–290. – ISBN 978-3-031-73364-2. DOI: 10.1007/978-3-031-73365-9_19 Scopus OpenAlex
Dates:
| Published print: | Dec 20, 2024 |
| Published online: | Dec 20, 2024 |
Identifiers:
| Scopus: | 2-s2.0-85214197940 |
| OpenAlex: | W4405599359 |
Citing:
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