Abstract
This paper presents the usage of a multi-objective genetic algorithm to a set of engineering design problems. The studied problems span from detailed design of a hydraulic pump to more comprehensive system design. Furthermore, the problems are modeled using dynamic simulation models, response surfaces based on FE-models as well as static equations. The proposed method is simple and straight forward and it does not require any problem specific parameter tuning. The studied problems have all been successfully solved with the same algorithm without any problem specific parameter tuning. The resulting Pareto frontiers have proven very illustrative and supportive for the decision-maker.
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Andersson, J. (2003). Applications of a Multi-objective Genetic Algorithm to Engineering Design Problems. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Thiele, L., Deb, K. (eds) Evolutionary Multi-Criterion Optimization. EMO 2003. Lecture Notes in Computer Science, vol 2632. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36970-8_52
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DOI: https://doi.org/10.1007/3-540-36970-8_52
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