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|Title:||Dynamic bi-objective routing of multiple vehicles|
|Citation:||Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO'20), 2020 / vol.abs/2005.13872, pp.166-174|
|Publisher:||Association for Computing Machinery|
|Publisher Place:||New York|
|Conference Name:||Genetic and Evolutionary Computation Conference (GECCO) (08 Jul 2020 - 12 Jul 2020 : Cancún Mexico)|
|Jakob Bossek, Christian Grimme, Heike Trautmann|
|Abstract:||In practice, e.g. in delivery and service scenarios, Vehicle-Routing- Problems (VRPs) often imply repeated decision making on dynamic customer requests. As in classical VRPs, tours have to be planned short while the number of serviced customers has to be maximized at the same time resulting in a multi-objective problem. Beyond that, however, dynamic requests lead to the need for re-planning of not yet realized tour parts, while already realized tour parts are irreversible. In this paper we study this type of bi-objective dynamic VRP including sequential decision making and concurrent realization of decisions. We adopt a recently proposed Dynamic Evolutionary Multi-Objective Algorithm (DEMOA) for a related VRP problem and extend it to the more realistic (here considered) scenario of multiple vehicles.We empirically showthat our DEMOA is competitive with a multi-vehicle offline and clairvoyant variant of the proposed DEMOA as well as with the dynamic single-vehicle approach proposed earlier.|
|Keywords:||Vehicle routing; decision making; multi-objective optimization; dynamic optimization; evolutionary algorithms|
|Rights:||© 2020 Copyright held by the owner/author(s). Publication rights licensed to ACM|
|Appears in Collections:||Computer Science publications|
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