Title :
Optimising Home Automation Systems: A comparative study on Tabu Search and Evolutionary Algorithms
Author :
Morganti, G. ; Perdon, A.M. ; Conte, G. ; Scaradozzi, D. ; Brintrup, A.
Author_Institution :
Dipt. di Ing. Inf., Gestionale e dell´´Autom., Univ. Politec. delle Marche, Ancona, Italy
Abstract :
We use the Multi Agent System paradigm to model and analyse Home Automation System performance in exploiting limited resources such as electricity and hot water. In this paper we evaluate several approaches to the optimisation of Home Automation System performance using Tabu Search, and Single and Multi-objective Genetic Algorithms. The results show that the Genetic Algorithms achieve faster convergence than Tabu Search. Multi-objective Genetic Algorithm provides a diverse set of solutions for the decision maker.
Keywords :
genetic algorithms; home automation; multi-agent systems; search problems; evolutionary algorithms; home automation systems; multi agent system; multi-objective genetic algorithms; tabu search; Automatic control; Boilers; Evolutionary computation; Genetic algorithms; Home appliances; Home automation; Performance analysis; Resource management; System performance; Water resources;
Conference_Titel :
Control and Automation, 2009. MED '09. 17th Mediterranean Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
978-1-4244-4684-1
Electronic_ISBN :
978-1-4244-4685-8
DOI :
10.1109/MED.2009.5164684
