loading
Papers

Research.Publish.Connect.

Paper

Authors: Limeme Ben Ali 1 ; Maher Helaoui 2 and Wady Naanaa 3

Affiliations: 1 Faculty of Economics and Management of Sfax, University of Sfax and Tunisia ; 2 Higher Institute of Business Administration, University of Gafsa and Tunisia ; 3 National Engineering School of Tunis, University Tunis El Manar and Tunisia

ISBN: 978-989-758-350-6

Keyword(s): Multi-objective Optimization, Multi-objective Valued Constraint Satisfaction Problems MO-VCSP, Soft Local Arc Consistency, Lower Bound Set, Pareto Dominance.

Related Ontology Subjects/Areas/Topics: AI and Creativity ; Artificial Intelligence ; Constraint Satisfaction ; Knowledge Representation and Reasoning ; Soft Computing ; Symbolic Systems

Abstract: A valued constraint satisfaction problem (VCSP) is a soft constraint framework that can formalize a wide range of applications related to Combinatorial Optimization and Artificial Intelligence. Most researchers have focused on the development of algorithms for solving mono-objective problems. However, many real-world satisfaction/optimization problems involve multiple objectives that should be considered separately and satisfied/optimized simultaneously. Solving a Multi-Objective Optimization Problem (MOP) consists of finding the set of all non-dominated solutions, known as the Pareto Front. In this paper, we introduce multi-objective valued constraint satisfaction problem (MO-VCSP), that is a VCSP involving multiple objectives, and we extend soft local arc consistency methods, which are widely used in solving Mono-Objective VCSP, in order to deal with the multi-objective case. Also, we present multi-objective enforcing algorithms of such soft local arc consistencies taking into accou nt the Pareto principle. The new Pareto-based soft arc consistency (P-SAC) algorithms compute a Lower Bound Set of the efficient frontier. As a consequence, P-SAC can be integrated into a Multi-Objective Branch and Bound (MO-BnB) algorithm in order to ensure its pruning efficiency. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.233.226.151

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Ben Ali, Limeme; Helaoui, M. and Naanaa, W. (2019). Pareto-based Soft Arc Consistency for Multi-objective Valued CSPs.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 294-305. DOI: 10.5220/0007401802940305

@conference{icaart19,
author={Ben Ali, Limeme and Maher Helaoui. and Wady Naanaa.},
title={Pareto-based Soft Arc Consistency for Multi-objective Valued CSPs},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={294-305},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007401802940305},
isbn={978-989-758-350-6},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Pareto-based Soft Arc Consistency for Multi-objective Valued CSPs
SN - 978-989-758-350-6
AU - Ben Ali, Limeme
AU - Helaoui, M.
AU - Naanaa, W.
PY - 2019
SP - 294
EP - 305
DO - 10.5220/0007401802940305

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.