Title :
Evolving agents in a market simulation platform - a test for distinct meta-heuristics
Author :
Oo, Naing Win ; Miranda, Vladimiro
Author_Institution :
INESC, Porto
Abstract :
This paper presents a comparison in performance of 3 variants of genetic algorithms (GA) vs. 2 variants of evolutionary particle swarm optimization (EPSO), made in the extremely complex context of a multi-energy market simulation where the behavior of energy retailers is observed. The simulations are on JADE, a FIPA compliant platform based on intelligent autonomous agents running in a cluster of PCs. Each agent formulates its strategy by an inner complex simulation process using a meta-heuristic that tries to define optimum decisions. The results suggest that an EPSO approach is more efficient than GA
Keywords :
genetic algorithms; multi-agent systems; particle swarm optimisation; power markets; power system simulation; FIPA compliant platform; JADE; complex simulation process; distinct meta-heuristics; energy retailers; evolutionary particle swarm optimization; evolving agents; genetic algorithms; intelligent autonomous agents; multienergy market simulation; Autonomous agents; Business; Energy consumption; Energy conversion; Genetic algorithms; Heating; Intelligent agent; Particle swarm optimization; Power system simulation; Testing;
Conference_Titel :
Intelligent Systems Application to Power Systems, 2005. Proceedings of the 13th International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
1-59975-174-7
DOI :
10.1109/ISAP.2005.1599311
