6533b7d8fe1ef96bd126afc5
RESEARCH PRODUCT
Drivers-Inspired Ants for Solving the Vehicle Routing Problem with Time Windows
Eric BusvelleStéphane MillotJean-baptiste VioixDalicia Bouallouchesubject
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO ] Computer Science [cs]Operations researchComputer scienceHeuristic (computer science)0211 other engineering and technologies02 engineering and technology[INFO] Computer Science [cs]Pledge[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Software[ SPI.NRJ ] Engineering Sciences [physics]/Electric powerVehicle routing problem0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]SimulationContinuous optimization021103 operations researchbusiness.industryAnt colony optimization algorithms[SPI.NRJ]Engineering Sciences [physics]/Electric powerSoftware development[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsTerm (time)020201 artificial intelligence & image processingbusiness[SPI.NRJ] Engineering Sciences [physics]/Electric powerdescription
International audience; 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.
year | journal | country | edition | language |
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2016-12-06 |