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

Tom Kent; Arthur Richards

doi:10.1145/3319619.3321993

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

Tom Kent, Arthur Richards

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

2 Citations (Scopus)

308 Downloads (Pure)

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.

Original language	English
Title of host publication	GECCO'19
Subtitle of host publication	Proceedings of the Genetic and Evolutionary Computation Conference Companion
Place of Publication	New York, NY, USA
Publisher	Association for Computing Machinery (ACM)
Pages	147-148
Number of pages	2
Volume	2019
ISBN (Electronic)	9781450367486
DOIs	https://doi.org/10.1145/3319619.3321993
Publication status	Accepted/In press - 21 Mar 2019
Event	The Genetic and Evolutionary Computation Conference 2019 - Prague, Prague, Czech Republic Duration: 13 Jul 2019 → 17 Jul 2019

Conference

Conference	The Genetic and Evolutionary Computation Conference 2019
Abbreviated title	GECCO 2019
Country/Territory	Czech Republic
City	Prague
Period	13/07/19 → 17/07/19

Keywords

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

Access to Document

10.1145/3319619.3321993

Full-text PDF (accepted author manuscript)
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

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Cite this

@inproceedings{bd21063d04fe4ad59fb99d8b12b8c618,

title = "Decentralised Multi-Demic Evolutionary Approach to the Dynamic Multi-Agent Travelling Salesman Problem",

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.",

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

author = "Tom Kent and Arthur Richards",

year = "2019",

month = mar,

day = "21",

doi = "10.1145/3319619.3321993",

language = "English",

volume = "2019",

pages = "147--148",

booktitle = "GECCO'19",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

note = "The Genetic and Evolutionary Computation Conference 2019, GECCO 2019 ; Conference date: 13-07-2019 Through 17-07-2019",

}

Kent, T & Richards, A 2019, Decentralised Multi-Demic Evolutionary Approach to the Dynamic Multi-Agent Travelling Salesman Problem. in GECCO'19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. vol. 2019, Association for Computing Machinery (ACM), New York, NY, USA, pp. 147-148, The Genetic and Evolutionary Computation Conference 2019, Prague, Czech Republic, 13/07/19. https://doi.org/10.1145/3319619.3321993

Decentralised Multi-Demic Evolutionary Approach to the Dynamic Multi-Agent Travelling Salesman Problem. / Kent, Tom; Richards, Arthur.
GECCO'19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. Vol. 2019 New York, NY, USA: Association for Computing Machinery (ACM), 2019. p. 147-148.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Decentralised Multi-Demic Evolutionary Approach to the Dynamic Multi-Agent Travelling Salesman Problem

AU - Kent, Tom

AU - Richards, Arthur

PY - 2019/3/21

Y1 - 2019/3/21

N2 - 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.

AB - 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.

KW - Multi Agent Travelling Salesman

KW - Evolutionary Algorithms

KW - Allo-cation and Routing

KW - Distributed problem solving

KW - Decision Making

UR - https://arxiv.org/abs/1906.05616

U2 - 10.1145/3319619.3321993

DO - 10.1145/3319619.3321993

M3 - Conference Contribution (Conference Proceeding)

VL - 2019

SP - 147

EP - 148

BT - GECCO'19

PB - Association for Computing Machinery (ACM)

CY - New York, NY, USA

T2 - The Genetic and Evolutionary Computation Conference 2019

Y2 - 13 July 2019 through 17 July 2019

ER -

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

Abstract

Conference

Keywords

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

Abstract

Conference

Keywords

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Other files and links

Fingerprint

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T-B PHASE: Prosperity Partnership with Thales

Cite this