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A survey on combinatorial optimizationin dynamic environments∗

Published online by Cambridge University Press:  16 December 2011

Nicolas Boria  and
Vangelis T. Paschos
Nicolas Boria
Affiliation:
LAMSADE, CNRS UMR 7243 and Université Paris-Dauphine, Place du Maréchal de Lattre de Tassigny, 75775 Paris Cedex 16, France. [email protected]
Vangelis T. Paschos
Affiliation:
LAMSADE, CNRS UMR 7243 and Université Paris-Dauphine, Place du Maréchal de Lattre de Tassigny, 75775 Paris Cedex 16, France. [email protected] Institut Universitaire de France 
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Abstract

This survey presents major results and issues related to the study of NPO problems in dynamic environments, that is, in settings where instances are allowed to undergo some modifications over time. In particular, the survey focuses on two complementary frameworks. The first one is the reoptimization framework, where an instance I that is already solved undergoes some local perturbation. The goal is then to make use of the information provided by the initial solution to compute a new solution. The second framework is probabilistic optimization, where the instance to optimize is not fully known at the time when a solution is to be proposed, but results from a determined Bernoulli process. Then, the goal is to compute a solution with optimal expected value.

Keywords

Approximationreoptimizationhereditary problemcomplexitygraphon-line algorithmsprobabilistic optimization
Type
Research Article
Information
RAIRO - Operations Research , Volume 45 , Issue 3 , July 2011 , pp. 241 - 294
Copyright
© EDP Sciences, ROADEF, SMAI 2011

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