Cabello, J. M. ; Cejudo, J. M. ; Luque, M. ; Ruiz, F. ; Deb, K. ; Tewari, R. (2009) Optimization of the sizing of a solar thermal electricity plant: mathematical programming versus genetic algorithms Proceedings of the Congress on Evolutionary Computation (CEC-2009), Piscatway, NJ: IEEE Press . pp. 1193-1200.
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Official URL: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arn...
Related URL: http://dx.doi.org/10.1109/CEC.2009.4983081
Abstract
Genetic algorithms (GAs) have been argued to constitute a flexible search thereby enabling to solve difficult problems which classical optimization methodologies may find hard to solve. This paper is intended towards this direction and show a systematic application of a GA and its modification to solve a real-world optimization problem of sizing a solar thermal electricity plant. Despite the existence of only three variables, this problem exhibits a number of other common difficulties-black-box nature of solution evaluation, massive multi-modality, wide and non-uniform range of variable values, and terribly rugged function landscape-which prohibits a classical optimization method to find even a single acceptable solution. Both GA implementations perform well and a local analysis is performed to demonstrate the optimality of obtained solutions. This study considers both classical and genetic optimization on a fairly complex yet typical real-world optimization problems and demonstrates the usefulness and future of GAs in applied optimization activities in practice.
Item Type: | Article |
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Source: | Copyright of this article belongs to Proceedings of the Congress on Evolutionary Computation (CEC-2009), Piscatway, NJ: IEEE Press. |
ID Code: | 81637 |
Deposited On: | 07 Feb 2012 03:50 |
Last Modified: | 18 May 2016 23:06 |
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