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| HAL: inria-00563668, version 1 |
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| Evostar, Turin : Italie (2011) |
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| Optimization of the Nested Monte-Carlo Algorithm on the Traveling Salesman Problem with Time Windows |
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| Arpad Rimmel 1Fabien Teytaud 2, 3 |
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| (2011-02-05) |
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| The traveling salesman problem with time windows is known to be a really difficult benchmark for optimization algorithms. In this paper, we are interested in the minimization of the travel cost. To solve this problem, we propose to use the nested Monte-Carlo algorithm combined with a Self-Adaptation Evolution Strategy. We compare the efficiency of several fitness functions. We show that with our technique we can reach the state of the art solutions for a lot of problems in a short period of time. |
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| 1: | Université Paris 9, Dauphine (UP9) |
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Université Paris IX - Paris Dauphine |
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| 2: | Laboratoire de Recherche en Informatique (LRI) |
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CNRS : UMR8623 – Université Paris XI - Paris Sud |
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| 3: | TAO (INRIA Saclay - Ile de France) |
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INRIA – CNRS : UMR8623 – Université Paris XI - Paris Sud |
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| Domain | : | Computer Science/Learning Mathematics/Optimization and Control |
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| inria-00563668, version 1 | |
| http://hal.inria.fr/inria-00563668 | |
| oai:hal.inria.fr:inria-00563668 | |
| From: Fabien Teytaud | |
| Submitted on: Monday, 7 February 2011 10:31:41 | |
| Updated on: Monday, 7 February 2011 10:44:08 | |
