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Application of the Nested Rollout Policy Adaptation Algorithm to the Traveling Salesman Problem with Time Windows
Abstract : In this paper, we are interested in the minimization of the travel cost of the traveling salesman problem with time windows. In order to do this minimization we use a Nested Rollout Policy Adaptation (NRPA) algorithm. NRPA has multiple levels and maintains the best tour at each level. It consists in learning a rollout policy at each level. We also show how to improve the original algorithm with a modified rollout policy that helps NRPA to avoid time windows violations.
Cited literature [16 references]
https://hal.inria.fr/hal-01406457
Contributor : Fabien Teytaud <>
Submitted on : Thursday, December 1, 2016 - 11:15:25 AM
Last modification on : Thursday, January 21, 2021 - 10:54:03 PM
Long-term archiving on: : Tuesday, March 21, 2017 - 12:58:20 PM
Contributor : Fabien Teytaud <>
Submitted on : Thursday, December 1, 2016 - 11:15:25 AM
Last modification on : Thursday, January 21, 2021 - 10:54:03 PM
Long-term archiving on: : Tuesday, March 21, 2017 - 12:58:20 PM
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tsptwnrpa.pdf
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