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Decentralised Multi-Demic Evolutionary Approach to the Dynamic Multi-Agent Travelling Salesman Problem

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

Original languageEnglish
Title of host publicationGECCO'19
Subtitle of host publicationProceedings of the Genetic and Evolutionary Computation Conference Companion
Place of PublicationNew York, NY, USA
Publisher or commissioning bodyAssociation for Computing Machinery (ACM)
Pages147-148
Number of pages2
Volume2019
ISBN (Electronic)9781450367486
DOIs
DateAccepted/In press - 21 Mar 2019
EventThe Genetic and Evolutionary Computation Conference 2019 - Prague, Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019

Conference

ConferenceThe Genetic and Evolutionary Computation Conference 2019
Abbreviated titleGECCO 2019
CountryCzech Republic
CityPrague
Period13/07/1917/07/19

Abstract

This paper looks to use both centralised and decentralised implementations of Evolutionary Algorithms to solve a dynamic variant of the Multi-Agent Travelling Salesman Problem. The problem is allocating an active set of tasks to a set of agents whilst simultaneously planning the route for each agent. The allocation and routing are closely coupled parts of the same problem, this paper attempts to align the real world implementation demands of a decentralised solution by using multiple populations with well defined interactions to exploit the problem structure.

    Research areas

  • Multi Agent Travelling Salesman, Evolutionary Algorithms, Allo-cation and Routing, Distributed problem solving, Decision Making

Event

The Genetic and Evolutionary Computation Conference 2019

Abbreviated titleGECCO 2019
Duration13 Jul 201917 Jul 2019
Location of eventPrague
CityPrague
CountryCzech Republic

Event: Conference

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Documents

  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via ACM at https://dl.acm.org/citation.cfm?id=3321993. Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 713 KB, PDF document

DOI

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