Multi-objective evolutionary optimization of sandwich structures: An evaluation by elitist non-dominated sorting evolution strategy

A. B. Ilyani Akmar, O. Kramer, Timon Rabczuk

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In this study, an application of evolutionary multi-objective optimization algorithms on the optimization of sandwich structures is presented. The solution strategy is known as Elitist Non-Dominated Sorting Evolution Strategy (ENSES) wherein Evolution Strategies (ES) as Evolutionary Algorithm (EA) in the elitist Non-dominated Sorting Genetic algorithm (NSGA-II) procedure. Evolutionary algorithm seems a compatible approach to resolve multi-objective optimization problems because it is inspired by natural evolution, which closely linked to Artificial Intelligence (AI) techniques and elitism has shown an important factor for improving evolutionary multi-objective search. In order to evaluate the notion of performance by ENSES, the well-known study case of sandwich structures are reconsidered. For Case 1, the goals of the multi-objective optimization are minimization of the deflection and the weight of the sandwich structures. The length, the core and skin thicknesses are the design variables of Case 1. For Case 2, the objective functions are the fabrication cost, the beam weight and the end deflection of the sandwich structures. There are four design variables i.e., the weld height, the weld length, the beam depth and the beam width in Case 2. Numerical results are presented in terms of Paretooptimal solutions for both evaluated cases.

Original languageEnglish
Pages (from-to)185-201
Number of pages17
JournalAmerican Journal of Engineering and Applied Sciences
Volume8
Issue number1
DOIs
Publication statusPublished - 2015 Apr 22
Externally publishedYes

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Keywords

  • Elitist non-dominated sorting evolution strategy (ENSES)
  • Evolutionary algorithm
  • Multi-objective evolutionary optimization
  • Pareto-optimal solutions
  • Sandwich structure

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science(all)
  • Chemical Engineering(all)
  • Geotechnical Engineering and Engineering Geology
  • Energy Engineering and Power Technology
  • Environmental Engineering

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