A survey on combinatorial optimization  in dynamic environments

A survey on combinatorial optimization in dynamic environments

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Article ID: iaor20127591
Volume: 45
Issue: 3
Start Page Number: 241
End Page Number: 294
Publication Date: Jul 2011
Journal: RAIRO - Operations Research
Authors: ,
Keywords: programming: dynamic
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.

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