Integrated Genetic Algorithm for Optimization of Space Structures
Publication: Journal of Aerospace Engineering
Volume 6, Issue 4
Abstract
Gradient‐based mathematical‐optimization algorithms usually seek a solution in the neighborhood of the starting point. If more than one local optimum exists, the solution will depend on the choice of the starting point, and the global optimum cannot be found. This paper presents the optimization of space structures by integrating a genetic algorithm with the penalty‐function method. Genetic algorithms are inspired by the basic mechanism of natural evolution, and are efficient for global‐searches. The technique employs the Darwinian survival‐of‐the‐fittest theory to yield the best or better characters among the old population, and performs a random information exchange to create superior offspring. Different types of crossover operations are used in this paper, and their relative merit is investigated. The integrated genetic algorithm has been implemented in C language and is applied to optimization of three space truss structures. In each case, an optimum solution was obtained after a limited number of iterations.
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Information & Authors
Information
Published In
Journal of Aerospace Engineering
Volume 6 • Issue 4 • October 1993
Pages: 315 - 328
Copyright
Copyright © 1993 American Society of Civil Engineers.
History
Received: Feb 7, 1992
Published online: Oct 1, 1993
Published in print: Oct 1993
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