Abstract
In practical optimal design problems, objective functions often lead to multimodal domains. There are generally two basic requirements in the multimodal function optimization problem:
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1.
to find the global optimum, i.e. global search ability, and
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2.
to locate several local optima that might be good alternatives to the global optimum, i.e. multi-optimum search ability.
The first one comes from the requirement of optimality, while the second one reflects the needs of practical engineering design. Multiple solutions permit designers to choose the best one in terms of ease of manufacture, ease of maintenance, reliability, etc, which cannot be simply represented by the objective function [2].
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Ling, Q., Wu, G., Wang, Q. (2008). Multimodal Function Optimization of Varied-Line-Spacing Holographic Grating. In: Hingston, P.F., Barone, L.C., Michalewicz, Z. (eds) Design by Evolution. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74111-4_17
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