Multiobjective evolutionary algorithm MOEA an approach for solving MAS multiatribute allocation task

Author

Mauledoux, Mauricio ; Shkodyrev, Viacheslav

Author_Institution

Distrib. Intell. Syst. Dept., State Polytech. Univ., St. Petersburg, St. Petersburg, Russia

Volume

1

fYear

2010

fDate

26-28 Feb. 2010

Firstpage

277

Lastpage

280

Abstract

The work is devoted to solve distributed task allocation task problem in group of agents with multi-objective genetic algorithms. The paper introduce the approach to select the correct stopping criterion for multi-objective genetic algorithms and the way to apply a new genetic operator using the solution information of the other agents for save time in the search of the optimal space in a group of agents.

Keywords

distributed processing; genetic algorithms; multi-agent systems; MAS multiatribute allocation task; MOEA; distributed task allocation task problem; genetic operator; multiobjective evolutionary algorithm; multiobjective genetic algorithm; stopping criterion; Aggregates; Artificial intelligence; Decision making; Evolutionary computation; Genetic algorithms; Intelligent agent; Intelligent systems; Pareto optimization; Stochastic processes; Uncertainty; Genetic algorithms; Multi agent system; component; multi-objective optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-5585-0

Electronic_ISBN

978-1-4244-5586-7

Type

conf

DOI

10.1109/ICCAE.2010.5451953

Filename

5451953