A new distributed particle swarm optimization algorithm for constraint reasoning

Authors:
Sadok Bouamama
Affiliations:
SOIE Laboratory, University of Tunis, Higher school of technology and informatics of Carthage
Venue:
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Year:
2010

Citing 4
Cited 1

An elitist distributed particle swarm algorithm for RF IC optimization

Proceedings of the 2005 Asia and South Pacific Design Automation Conference
Swarm intelligence on the binary constraint satisfaction problem

CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Valued constraint satisfaction problems: hard and easy problems

IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Comparing evolutionary algorithms on binary constraint satisfaction problems

IEEE Transactions on Evolutionary Computation

A New Hybrid Distributed Double Guided Genetic Swarm Algorithm for Optimization and Constraint Reasoning: Case of Max-CSPs

International Journal of Swarm Intelligence Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

Within the framework of constraint reasoning we introduce a newer distributed particle swarm approach. The latter is a new multi-agent approach which addresses additive Constraint Satisfaction problems (ΣCSPs). It is inspired by the dynamic distributed double guided genetic algorithm (D3G2A) for Constraint reasoning. It consists of agents dynamically created and cooperating in order to solve problems. Each agent performs locally its own particle swarm optimization algorithm (PSO). This algorithm is slightly different from other PSO algorithms. As well, not only do the new approach parameters allow diversification but also permit escaping from local optima. Second,. Experimentations are held to show effectiveness of our approach.