Engineering optimizations using the structured genetic algorithm
Dipankar Dasgupta, Douglas R. McGregor · 1992
. This paper discusses the application of a new genetic search approach called the Structured Genetic Algorithm (sGA) for solving engineering optimization problems. The novelity of this genetic model lies in its hierarchical genomic structure and a gene activation mechanism in its chromosome. Simulation results exhibit its robustness in finding global optima. 1 Introduction. Genetic Algorithms (GA)[5] are adaptive search techniques which simulate both natural inheritance by genetics and a Darwinian struggle for survival; they have been successfully used in a wide range of optimization problems. With the increasing applications of Genetic Algorithms, many modifications have been suggested to improve its performance in solving non-linear and multiple-solution problems. Our recently developed Structured Genetic Algorithm(sGA)[1] is more efficient in solving complex problems than simple GA. 2 The Structured Genetic Algorithm. The central feature of sGA[1] is its use of genetic redundan...