Multi-objective evolutionary algorithm application on the welded beam design problem

Optimization algorithms may be applied for solving engineering design problems. In this study, two different evolutionary algorithms are applied to solve the multi objective welded beam design problem. These are; the multi-objective hyper heuristics evolutionary algorithm (MHypEA) and the fast and e...

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Veröffentlicht in:	2022 30th Signal Processing and Communications Applications Conference (SIU) S. 1 - 4
1. Verfasser:	Alp, Gozde
Format:	Tagungsbericht
Sprache:	Englisch Türkisch
Veröffentlicht:	IEEE 15.05.2022
Schlagworte:	evolutionary algorithms Evolutionary computation Genetic algorithms Multi objective optimization Optimization Signal processing Signal processing algorithms Sorting welded beam design problem Welding
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Zusammenfassung:	Optimization algorithms may be applied for solving engineering design problems. In this study, two different evolutionary algorithms are applied to solve the multi objective welded beam design problem. These are; the multi-objective hyper heuristics evolutionary algorithm (MHypEA) and the fast and elitist non-dominated sorting genetic algorithm (NSGA-II). Due to the nature of the problem, the algorithm performances are compared in terms of hyper volume and inverted generational distance indicators, which are used in the evaluation of multi-objective optimization techniques. Experimental results show that NSGA-II is %2 and %28 better than MHypEA on the average for solving the welded beam design problem in terms of hyper-volume and inverted generational distance indicators respectively. The results encourages the utilization of evolutionary algorithms in solving engineering design problems.
DOI:	10.1109/SIU55565.2022.9864808