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Algorithm and knowledge engineering for the TSPTW problem
Abstract : In this paper we consider knowledge and algorithm
engineering in combinatorial optimization for improved solving of
complex TSPs with Time Windows. In addition to Nested MonteCarlo
Search with Policy Adaption, as invented by Rosin (2011)
and applied to TSP by Cazenave and Teytaud (2012), among
other refinements to speed-up the exploration we perform beam
search for an improved compromise of search breadth and depth
and automated knowledge elicitation to seed the distribution
for the exploration. We show promising results on TSPTW
benchmarks and indicate improvements for real-world logistics
scenarios by using a multiagent simulation system with each
agent computing and trading their individual TSPTW solutions
Cited literature [23 references]
https://hal.inria.fr/hal-01406484
Contributor : Fabien Teytaud <>
Submitted on : Thursday, December 1, 2016 - 11:45:00 AM
Last modification on : Monday, July 19, 2021 - 2:50:42 PM
Long-term archiving on: : Thursday, March 23, 2017 - 12:00:29 AM
Contributor : Fabien Teytaud <>
Submitted on : Thursday, December 1, 2016 - 11:45:00 AM
Last modification on : Monday, July 19, 2021 - 2:50:42 PM
Long-term archiving on: : Thursday, March 23, 2017 - 12:00:29 AM
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tsptw.pdf
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