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Authors: Julien Martin 1 ; Jean-Pierre Georgé 1 ; Marie-Pierre Gleizes 1 and Mickaël Meunier 2

Affiliations: 1 IRIT, France ; 2 SNECMA Villaroche, France

Keyword(s): Pareto Front, Adaptive Multi-Agent System, Multi-Objective Optimization

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Autonomous Systems ; Cooperation and Coordination ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Multi-Agent Systems ; Software Engineering ; State Space Search ; Symbolic Systems

Abstract: Multidisciplinary Design Optimization (MDO) problems can have a unique objective or be multi-objective. In this paper, we are interested in MDO problems having at least two conflicting objectives. This characteristic ensures the existence of a set of compromise solutions called Pareto front. We treat those MDO problems like Multi-Objective Optimization (MOO) problems. Actual MOO methods suffer from certain limitations, especially the necessity for their users to adjust various parameters. These adjustments can be challenging, requiering both disciplinary and optimization knowledge. We propose the use of the Adaptive Multi-Agent Systems technology in order to automatize the Pareto front obtention. ParetOMAS (Pareto Optimization Multi-Agent System) is designed to scan Pareto fronts efficiently, autonomously or interactively. Evaluations on several academic and industrial test cases are provided to validate our approach.

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Paper citation in several formats:
Martin, J.; Georgé, J.; Gleizes, M. and Meunier, M. (2015). Autonomous Pareto Front Scanning using an Adaptive Multi-Agent System for Multidisciplinary Optimization. In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-073-4; ISSN 2184-433X, SciTePress, pages 263-271. DOI: 10.5220/0005293302630271

@conference{icaart15,
author={Julien Martin. and Jean{-}Pierre Georgé. and Marie{-}Pierre Gleizes. and Mickaël Meunier.},
title={Autonomous Pareto Front Scanning using an Adaptive Multi-Agent System for Multidisciplinary Optimization},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2015},
pages={263-271},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005293302630271},
isbn={978-989-758-073-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Autonomous Pareto Front Scanning using an Adaptive Multi-Agent System for Multidisciplinary Optimization
SN - 978-989-758-073-4
IS - 2184-433X
AU - Martin, J.
AU - Georgé, J.
AU - Gleizes, M.
AU - Meunier, M.
PY - 2015
SP - 263
EP - 271
DO - 10.5220/0005293302630271
PB - SciTePress

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