Multi-objective optimization of laminated ceramic composites using genetic algorithms

A. D. Belegundu, D. V. Murthy, R. R. Salagame, E. W. Constans

Research output: Contribution to conferencePaper

24 Scopus citations

Abstract

In recent years, much interest has been generated for using genetic algorithms to optimize certain classes of problems. Genetic algorithms have definite advantages over some other types of optimization algorithms in that they are quite robust, and do not require knowledge of the gradients of the objective function. Because of their unique breeding and selection processes, genetic algorithms can be used with equal ease on linear and nonlinear optimization problems, which makes them an excellent all-purpose optimization algorithm. This paper will discuss a new genetic algorithm (GENMO) that can be used to simultaneously optimize multiple objectives. Specifically, the GENMO algorithm can be used to generate Pareto sets for two or more conflicting objective functions.

Original languageEnglish (US)
Pages1015-1022
Number of pages8
DOIs
StatePublished - Jan 1 1994
Event5th Symposium on Multidisciplinary Analysis and Optimization, 1994 - Panama City Beach, United States
Duration: Sep 7 1994Sep 9 1994

Other

Other5th Symposium on Multidisciplinary Analysis and Optimization, 1994
CountryUnited States
CityPanama City Beach
Period9/7/949/9/94

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Aerospace Engineering

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    Belegundu, A. D., Murthy, D. V., Salagame, R. R., & Constans, E. W. (1994). Multi-objective optimization of laminated ceramic composites using genetic algorithms. 1015-1022. Paper presented at 5th Symposium on Multidisciplinary Analysis and Optimization, 1994, Panama City Beach, United States. https://doi.org/10.2514/6.1994-4363