Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1237
Title: Genetic algorithms for design of liquid retaining structure
Authors: Chau, KW 
Albermani, F
Issue Date: 2002
Source: In T Hendtlas & M Ali (Eds.), Developments in applied artificial intelligence : 15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2002, Cairns, Australia, June 2002 : proceedings, p. 119-128. Berlin ; New York: Springer, 2002
Abstract: In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.
Keywords: Genetic algorithm
Liquids
Structural design
Publisher: Springer
ISBN: 978-3-540-43781-9
DOI: 10.1007/3-540-48035-8_12
Description: Series: Lecture notes in computer science
Rights: © Springer-Verlag Berlin Heidelberg 2002. The original publication is available at http://www.springerlink.com.
Appears in Collections:Book Chapter

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