Integer Programming Models and Metaheuristics for Customer Order Scheduling Conference Abstracts
| Conference |
XXIII International Conference Mathematical Optimization Theory and Operations Research 30 Jun - 6 Jul 2024 , Омск |
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| Source | MOTOR 2024: сборник тезисов XXIII Международной конференции «Теория математической оптимизации и исследование операций», (Омск, 30 июня – 06 июля 2024 г.) Compilation, Издательство ОмГУ. Омск.2024. 109 c. ISBN 978-5-7779-2691-3. |
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| Output data | Year: 2024, Pages: 106-107 Pages count : 2 | ||
| Tags | scheduling, algorithm, model, experiment. | ||
| Authors |
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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:
Zakharov A.
, Zakharova Y.
Integer Programming Models and Metaheuristics for Customer Order Scheduling
In compilation MOTOR 2024: сборник тезисов XXIII Международной конференции «Теория математической оптимизации и исследование операций», (Омск, 30 июня – 06 июля 2024 г.). – Издательство ОмГУ., 2024. – C.106-107. – ISBN 978-5-7779-2691-3.
Integer Programming Models and Metaheuristics for Customer Order Scheduling
In compilation MOTOR 2024: сборник тезисов XXIII Международной конференции «Теория математической оптимизации и исследование операций», (Омск, 30 июня – 06 июля 2024 г.). – Издательство ОмГУ., 2024. – C.106-107. – ISBN 978-5-7779-2691-3.
Dates:
| Published print: | Jul 17, 2024 |
| Published online: | Jul 17, 2024 |
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