Comparison of agent-based scheduling to look-ahead heuristics for real-time transportation problems

Research output: Working paper

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We consider the real-time scheduling of full truckload transportation orders with time windows that arrive during schedule execution. Because a fast scheduling method is required, look-ahead heuristics are traditionally used to solve these kinds of problems. As an alternative, we introduce an agent-based approach where intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. This approach offers several advantages: it is fast, requires relatively little information and facilitates easy schedule adjustments in reaction to information updates. We compare the agent-based approach to more traditional hierarchical heuristics in an extensive simulation experiment. We find that a properly designed multiagent approach performs as good as or even better than traditional methods. Particularly, the multi-agent approach yields less empty miles and a more stable service level.
Original languageUndefined
Place of PublicationEnschede
PublisherUniversity of Twente, Research School for Operations Management and Logistics (BETA)
Number of pages30
Publication statusPublished - 2005

Publication series

NameBeta working papers
PublisherBeta Research School for Operations Management and Logistics, University of Twente


  • Auctions/bidding
  • Transportation
  • IR-70236
  • Multi-Agent Systems

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