Abstract
Almost every optimization problem can be viewed as multi-objective one. Multi-objective problems with conflicting objectives lead to so called Pareto front which expresses trade-off among the objectives. Multi-objective techniques yield better understanding of the solved problem because resulting Pareto front expresses the balance between different objectives. In this chapter, fundamentals of multi-objective optimization are reviewed. Then, multi-objective optimization technique based on principle of self-organizing migration is described. The proposed method is able to solve unconstrained, constrained problems having any number of variables and objectives. The method is designed to find so called non-dominated set that covers the true Pareto front uniformly.
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Acknowledgements
Research described in this chapter was financially supported by Czech Science Foundation under grant no. P102/12/1274. Support of projects SIX CZ.1.05/2.1.00/03.0072 is also gratefully acknowledged.
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Kadlec, P., Raida, Z. (2016). Multi-objective Self-organizing Migrating Algorithm. In: Davendra, D., Zelinka, I. (eds) Self-Organizing Migrating Algorithm. Studies in Computational Intelligence, vol 626. Springer, Cham. https://doi.org/10.1007/978-3-319-28161-2_4
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DOI: https://doi.org/10.1007/978-3-319-28161-2_4
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