Affiliation:
1. Iran University of Science and Technology Tehran, Iran
Abstract
The application of a continuous ant algorithm for the optimal design of cascade stilling basins as a common means for energy dissipation is investigated. Ant colony optimisation (ACO) is a newly introduced metaheuristic algorithm for solving discrete optimisation problems. The algorithm is based on the behaviour of real ant colonies and has traditionally been used exclusively for solving problems in the discrete domain. Since the emergence of ant algorithms as an optimisation tool, some attempts have been made to use them for tackling continuous optimisation problems. This paper presents a specialised version of the ACO algorithm that is capable of searching continuous spaces and used for solving continuous optimisation problems. The objective is to investigate the efficiency of ACO by minimising the total cost of cascade stilling basin construction (a function of height of falls and length of the basin) while fulfilling hydraulic and topographical criteria. The proposed method is first tested against some well-known benchmark problems. The method is then used to optimally solve an engineering example (a cascade stilling basin, Tehri dam, India). The results are presented and compared with those of an existing conventional design method based on engineering judgement. The sensitivity of the proposed algorithm to the only parameter of the model is tested and the results are presented for the design example. The results indicate that the algorithm is capable of producing designs superior to the existing alternative method in all the cases considered.
Subject
Water Science and Technology
Cited by
1 articles.
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