Title :
Multi agent genetic decision support for projects scheduling
Author :
Aksyonov, K.A. ; Antonova, A.S.
Author_Institution :
Ural Fed. Univ. named after First President of Russia B.N. Yeltsin, Yekaterinburg, Russia
Abstract :
This paper focuses on the optimization of the projects scheduling problem decision using evolutionary computation and simulation. The multi agent genetic optimization method to solve the project scheduling problem base on the basis of the annealing simulation algorithm, novelty search algorithm, genetic algorithm and multi agent simulation.
Keywords :
decision support systems; genetic algorithms; multi-agent systems; project management; scheduling; search problems; simulated annealing; annealing simulation algorithm; evolutionary computation; genetic algorithm; multiagent genetic decision support; multiagent genetic optimization method; multiagent simulation; novelty search algorithm; project scheduling problem optimization; Biological cells; Genetic algorithms; Genetics; Job shop scheduling; Optimization; Search problems; Unified modeling language;
Conference_Titel :
Microwave and Telecommunication Technology (CriMiCo), 2013 23rd International Crimean Conference
Conference_Location :
Sevastopol
Print_ISBN :
978-966-335-395-1
