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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 354523, 12 pages
Review Article

Bio-Inspired Optimization of Sustainable Energy Systems: A Review

1College of Computer Science & Technology, Zhejiang University of Technology, Hangzhou 310023, China
2College of Life Sciences, Fujian Normal University, Fuzhou, Fujian 350108, China

Received 12 December 2012; Accepted 17 January 2013

Academic Editor: Maurizio Carlini

Copyright © 2013 Yu-Jun Zheng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Sustainable energy development always involves complex optimization problems of design, planning, and control, which are often computationally difficult for conventional optimization methods. Fortunately, the continuous advances in artificial intelligence have resulted in an increasing number of heuristic optimization methods for effectively handling those complicated problems. Particularly, algorithms that are inspired by the principles of natural biological evolution and/or collective behavior of social colonies have shown a promising performance and are becoming more and more popular nowadays. In this paper we summarize the recent advances in bio-inspired optimization methods, including artificial neural networks, evolutionary algorithms, swarm intelligence, and their hybridizations, which are applied to the field of sustainable energy development. Literature reviewed in this paper shows the current state of the art and discusses the potential future research trends.