Optimization of a demand responsive transport service using multi-objective evolutionary algorithms

Renan J. S. Viana, André G. Santos, Flávio V. C. Martins, Elizabeth F. Wanner

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

This paper addresses the problem of optimizing a Demand Responsive Transport (DRT) service. A DRT is a flexible transportation service that provides on-demand transport for users who formulate requests specifying desired locations and times of pick-up and delivery. The vehicle routing and scheduling procedures are performed based on a set of requests. This problem is modeled as a multi-objective Dial-a-Ride problem (DARP), in which a set of objectives related to costs and user inconvenience is optimized while respecting a set of constraints imposed by the passengers and vehicles, as time windows and capacity. The resulting model is solved by means of three Multi-objective Evolutionary Algorithms (MOEA) associated with feasibility-preserving operators. Computational experiments were performed on benchmark instances and the results were analyzed by means of performance quality indicators widely used for multi-objective algorithms comparison. The proposed approaches demonstrate efficient and higher performance when optimizing this DRT service compared to another algorithm from the literature.
Original languageEnglish
Title of host publicationGECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion
PublisherACM
Pages2064-2067
Number of pages4
ISBN (Electronic)9781450367486
ISBN (Print)978-1-4503-6748-6
DOIs
Publication statusPublished - 13 Jul 2019
Eventthe Genetic and Evolutionary Computation Conference Companion - Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019

Conference

Conferencethe Genetic and Evolutionary Computation Conference Companion
Period13/07/1917/07/19

Keywords

  • Demand Responsive Transport
  • Dial-a-Ride Problem
  • Multi-objective Evolutionary Algorithm

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