A Hybrid Approach Combining Local Search and Constraint Programming for a Large Scale Energy Management Problem
This paper presents a heuristic approach combining constraint satisfaction, local search and a constructive optimization algorithm for a large-scale energy management and maintenance scheduling problem. The methodology shows how to successfully combine and orchestrate different types of algorithms a...
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| Veröffentlicht in: | R.A.I.R.O. Recherche opérationnelle 2013-09, Vol.47 (4), p.481-500 |
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| container_title | R.A.I.R.O. Recherche opérationnelle |
| container_volume | 47 |
| creator | Gavranovic, Haris Buljubasic, Mirsad |
| description | This paper presents a heuristic approach combining constraint satisfaction, local search and a constructive optimization algorithm for a large-scale energy management and maintenance scheduling problem. The methodology shows how to successfully combine and orchestrate different types of algorithms and to produce competitive results. We also propose an efficient way to scale the method for huge instances. A large part of the presented work was done to compete in the ROADEF/EURO Challenge 2010, organized jointly by the ROADEF, EURO and Électricité de France. The numerical results obtained on official competition instances testify about the quality of the approach. The method achieves 3 out of 15 possible best results. |
| doi_str_mv | 10.1051/ro/2013053 |
| format | Article |
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| identifier | ISSN: 0399-0559 |
| ispartof | R.A.I.R.O. Recherche opérationnelle, 2013-09, Vol.47 (4), p.481-500 |
| issn | 0399-0559 1290-3868 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1677906204 |
| source | NUMDAM; Cambridge University Press Journals Complete |
| subjects | 68T20 90-08 90C10 90C59 Algorithms Competition constraint satisfaction Energy management local search Maintenance management Mathematical models Operations research Optimization Programming ROADEF challenge scheduling Searching |
| title | A Hybrid Approach Combining Local Search and Constraint Programming for a Large Scale Energy Management Problem |
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