Abstract
This chapter presents a paper that proposes a multiobjective evolutionary algorithm (MOEA) for structural optimization. The proposed approach emphasizes on efficiency and has been found to be competitive with respect to other MOEAs in current use. Evolutionary algorithms have become an increasingly popular design and optimization tool in the past few years, along with a constantly growing development of new algorithms and applications. New areas remain to be explored. One of them is the use of evolutionary algorithms to solve multiobjective optimization problems. In nature, most problems are multiobjective but are restated as single-objective optimization problems by transforming all the objectives, but one, into constraints. Evolutionary algorithms are desirable for solving multiobjective optimization problems because they deal simultaneously with a set of possible solutions, which allows finding many members of the Pareto optimal set in a single run of the algorithm.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
