Optimising Home Automation Systems: a Comparative Study on Tabu Search and Evolutionary Algorithms

被引：7
|
作者：
Morganti, G. [1 ]
Perdon, A. M. [1 ]
Conte, G. [1 ]
Scaradozzi, D. [1 ]
Brintrup, A. [2 ]
机构：
[1] Univ Politecn Marche, Dipartimento Ingn Informat Gest & Automaz, Via Brecce Bianche 12, I-60131 Ancona, Italy
[2] Univ Cambridge, Inst Mfg, Cambridge CB2 1RX, England
来源：
MED: 2009 17TH MEDITERRANEAN CONFERENCE ON CONTROL & AUTOMATION, VOLS 1-3 | 2009年
关键词：
D O I：
10.1109/MED.2009.5164684
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：1044 / 1049
页数：6
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