Drivers-Inspired Ants for Solving the Vehicle Routing Problem with Time Windows

Abstract : In our study, we develop a method that merges two information sources within ants colony optimization heuristic. Namely artificial ants which occurs for short term optimization and transporter's vehicles that occurs in long term and continuous optimization toward solving the real-world vehicle routing problem. This study is supported by a transporter (Upsilon) of the region of l'Yonne in France and a transport and logistics software development company (Tedies). Our method suits for transporters that use human planners to make decisions about their tours and intending to move to computer planners without drastically upsetting the drivers habits. Hence, the pledge of this study is to take advantage from transport operators practices to achieve solutions which are as close as possible to the real-world vehicle routing planning, and keep a human control on the way optimal paths are computed and applied.
Type de document :
Communication dans un congrès
IEEE Symposium Series on Computational Intelligence (IEEE SSCI), Dec 2016, Athènes, Greece. IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, PROCEEDINGS OF 2016 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2016, 〈http://ieeexplore.ieee.org/document/7850277/〉
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01552752
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : lundi 3 juillet 2017 - 11:01:50
Dernière modification le : mercredi 12 septembre 2018 - 01:26:35

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  • HAL Id : hal-01552752, version 1

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Dalicia Bouallouche, Jean-Baptiste Vioix,, Eric Busvelle, Millot Stéphane. Drivers-Inspired Ants for Solving the Vehicle Routing Problem with Time Windows. IEEE Symposium Series on Computational Intelligence (IEEE SSCI), Dec 2016, Athènes, Greece. IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, PROCEEDINGS OF 2016 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2016, 〈http://ieeexplore.ieee.org/document/7850277/〉. 〈hal-01552752〉

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