Dynamic Bi-Objective Routing of Multiple Vehicles

Jakob Bossek, Christian Grimme, Heike Trautmann

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


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 show that 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.
Original languageEnglish
Title of host publicationProceedings of the Genetic and Evolutionary Computation Conference (GECCO '20)
Place of PublicationCancun, Mexico
Number of pages9
Publication statusPublished - 2020
EventGenetic and Evolutionary Computation Conference, GECCO 2020 - Online Event, Cancun, Mexico
Duration: 8 Jul 202012 Jul 2020


ConferenceGenetic and Evolutionary Computation Conference, GECCO 2020
Abbreviated titleGECCO 2020


Dive into the research topics of 'Dynamic Bi-Objective Routing of Multiple Vehicles'. Together they form a unique fingerprint.

Cite this