Author(s)

C.Y. Lin & P. Hajela

Abstract

EVOLVE: A genetic search based optimization code with multiple strategies C.-Y. Lin\ P. HajeW "Mechanical Engineering, National Taiwan Institute of Technology, Taipei, Taiwan, Peoples Republic of China ^Mechanical Engineering, Aeronautical Engineering and Mechanics, Rensselaer Polytechnic Institute, Troy, New York, USA ABSTRACT The present paper describes the capabilities of a modern design optimization tool based on the method of genetic search. This stochastic search technique offers a significantly increased probability of locating the global optimum in a design space with multiple relative optima. The program includes an advanced search technique referred to as directed crossover wherein bit positions on the design strings that offer a higher gain during crossover are assigned higher probabilities of selection as crossover sites. Directed crossover is based on bitwise generational gradient to identify critical bit positions on the string, and prov

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