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Multi-Objective Optimization Problems

Part of the book series: SpringerBriefs in Mathematics ((BRIEFSMATH))

Abstract

In this chapter, the Self-adaptive Multi-objective Optimization Differential Evolution algorithm is applied to a series of engineering problems (beam with section I; welded beam; machinability of stainless steel; optimization of hydro cyclone performance; alkylation process optimization; batch stirred biochemical tank reactor; catalyst mixing; crystallization process; rotary dryer and rotor-dynamics design). The results obtained by the proposed methodology were compared with those obtained from other evolutionary strategies. In general, the proposed methodology was able to obtain the same quality of solution in comparison with other evolutionary strategies. In addition, the number of objective function evaluations required by the proposed algorithm was less than those required by other evolutionary algorithms.

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Authors and Affiliations

  1. School of Chemical Engineering, Federal University of Uberlândia, Uberlândia, Brazil

    Fran Sérgio Lobato

  2. School of Mechanical Engineering, Federal University of Uberlândia, Uberlândia, Brazil

    Valder Steffen Jr.

Authors
  1. Fran Sérgio Lobato
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  2. Valder Steffen Jr.
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Lobato, F.S., Steffen, V. (2017). Engineering. In: Multi-Objective Optimization Problems. SpringerBriefs in Mathematics. Springer, Cham. https://doi.org/10.1007/978-3-319-58565-9_6

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