Article

The DynCOAA algorithm for dynamic constraint optimization problems

Authors:

Koenraad Mertens,

Tom Holvoet,

Yolande BerbersAuthors Info & Claims

AAMAS '06: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems

Pages 1421 - 1423

https://doi.org/10.1145/1160633.1160898

Published: 08 May 2006 Publication History

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Abstract

Numerous problems in software coordination, operations research, manufacturing control and others can be transformed in constraint optimization problems (COPs). Moreover, most practical problems change constantly, requiring algorithms that can handle dynamic problems.In this paper we present the dynamic constraint optimization ant algorithm (DynCOAA) that can solve dynamic COPs. DynCOAA is specifically designed for dynamic problems, as it is based upon the ant colony optimization (ACO) meta-heuristic that has already proven its merit in other dynamic optimization problems. DynCOAA is a distributed algorithm that is suited for a one-on-one mapping between variables and hosts, but it can effectively accommodate multiple variables per host. We compared our algorithm to two existing algorithms for dynamic constraint optimization: DynAWC and DynDBA. We find that DynCOAA outperforms DynAWC and DynDBA on some problems, while remaining competitive on others.

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K. Mertens and T. Holvoet. CSAA; a Constraint Satisfaction Ant Algorithm Framework. In Proceedings of the Sixth International Conference on Adaptive Computing in Design and Manufacture (ACDM'04), pages 285--294. Springer-Verlag, 2004.

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K. Mertens and T. Holvoet. CSAA; a Distributed Ant Algorithm Framework for Constraint Satisfaction. In Proceedings of the 17th International FLAIRS Conference, pages 764--769. AAAI Press, 2004.

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Barambones JImbert RMoral C(2021)Applicability of Multi-Agent Systems and Constrained Reasoning for Sensor-Based Distributed Scenarios: A Systematic Mapping Study on Dynamic DCOPsSensors10.3390/s2111380721:11(3807)Online publication date: 31-May-2021
https://doi.org/10.3390/s21113807
SamadiDana S(2021)Exploring the Effect of Noisy Environment on Distributed Problem Solving2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)10.1109/CCWC51732.2021.9376129(0073-0080)Online publication date: 27-Jan-2021
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Published In

AAMAS '06: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems

May 2006

1631 pages

ISBN:1595933034

DOI:10.1145/1160633

General Chairs:
Hideyuki Nakashima
Future University - Hakodate, Japan
,
Michael Wellman
University of Michigan
,
Program Chairs:
Gerhard Weiss
Technical University Munich, Germany
,
Peter Stone
The University of Texas at Austin

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 08 May 2006

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AAMAS06: AAMAS '06 - 5th International Joint Conference on Autonomous Agents and Multi-agent Systems 2006

May 8 - 12, 2006

Japan, Hakodate

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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https://doi.org/10.1016/j.swevo.2024.101578
Barambones JImbert RMoral C(2021)Applicability of Multi-Agent Systems and Constrained Reasoning for Sensor-Based Distributed Scenarios: A Systematic Mapping Study on Dynamic DCOPsSensors10.3390/s2111380721:11(3807)Online publication date: 31-May-2021
https://doi.org/10.3390/s21113807
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https://doi.org/10.1109/CCWC51732.2021.9376129
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Mailler RZheng HRidgway A(2017)Dynamic, distributed constraint solving and thermodynamic theoryAutonomous Agents and Multi-Agent Systems10.1007/s10458-017-9377-532:1(188-217)Online publication date: 27-Jul-2017
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Mailler RZheng HBazzan AHuhns MLomuscio AScerri P(2014)A new analysis method for dynamic distributed constraint satisfactionProceedings of the 2014 international conference on Autonomous agents and multi-agent systems10.5555/2615731.2617390(901-908)Online publication date: 5-May-2014
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A hybrid genetic-particle swarm optimization algorithm for multi-constraint optimization problems

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