Traditional solution concepts for the vehicle routing problem (VRP) are pushed to their limits, when applied on dynamically changing vehicle routing scenarios-which are more close to reality than the static formulation. By contrast, the introduced distributed routing concept is designed to match packages and vehicles and to continuously make route decisions especially within a dynamic environment. In this autonomous control concept, each of these objects makes its own decisions. The developed algorithm was entitled Distributed Logistics Routing Protocol (DLRP). But in spite of the restricted suitability of the traditional VRP concepts for dynamic environments, they are still the benchmark for any VRPsimilar task. Therefore, we first present a description of the developed DLRP. Then an adapted vehicle routing problem is defined, which both sides, static and dynamic concepts, can cope with. Finally, both concepts are compared using a tabu search algorithm as a well working instance of traditional VRP-concepts. For a quantitative comparison, four solutions are given for the same adapted problem: the optimal solution as a lower bound, the DLRP solution, a tabu search solution and a random-like solution as an upper bound.
Abstract-In current transport logistics, routing is usually done centrally. A dedicated routing instance solves the optimisation problem of finding the best solution to handle the current set of orders with the set of available vehicles under constraints such as vehicle utilisation, punctuality etc. Because of the increasing complexity of logistic processes, approaches have been suggested recently which change this centralised routing paradigm towards a distributed approach with autonomous logistic entities (vehicles and goods) deciding on their own. To be able to obtain enough knowledge for reasonable decisions, the logistic entities have to communicate with each other. For this interaction, the information exchange concept DLRP (Distributed Logistic Routing Protocol) has been proposed before. The work presented in this paper will focus on the aspect of scalability of communication in a DLRP scenario. Message flooding is identified as potential challenge for the scalability of DLRP, and intelligent flooding restrictions to the communication traffic are applied.
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