A Generalized Consistent Neighborhood Search for Satellite Range Scheduling Problems
RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 1, pp. 99-121.

Many optimization problems require the use of a local search to find a satisfying solution in a reasonable amount of time, even if the optimality is not guaranteed. Usually, local search algorithms operate in a search space which contains complete solutions (feasible or not) to the problem. In contrast, in Consistent Neighborhood Search (CNS), after each variable assignment, the conflicting variables are deleted to keep the partial solution feasible, and the search can stop when all the variables have a value. In this paper, we propose a generalized version of CNS, discuss its performance according to various criteria, and present successful adaptations of CNS to three types of satellite range scheduling problems. Such problems are motivated by applications encountered by the French National Space and Aeronautic Agencies and the US Air Force Satellite Control Network. The described numerical experiments will demonstrate that CNS is a powerful and flexible method, which can be easily combined with efficient ingredients.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2014027
Classification : 9008
Mots clés : Metaheuristics, combinatorial optimization, satellite scheduling, consistent neighborhood search
Zufferey, Nicolas 1 ; Vasquez, Michel 2

1 Geneva School of Economics and Management, GSEM – University of Geneva, Uni-Mail, 1211 Geneva 4, Switzerland.
2 École des Mines d’Alès, LGI2P Research Center, Site EERIE, Parc scientifique Georges Besse, 30035 Nimes Cedex 01, France.
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Zufferey, Nicolas; Vasquez, Michel. A Generalized Consistent Neighborhood Search for Satellite Range Scheduling Problems. RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 1, pp. 99-121. doi : 10.1051/ro/2014027. http://www.numdam.org/articles/10.1051/ro/2014027/

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