Multi-objective Self-organizing Migrating Algorithm

  • Petr KadlecEmail author
  • Zbyněk Raida
Part of the Studies in Computational Intelligence book series (SCI, volume 626)


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.


Pareto Front Objective Space Decision Space Extreme Solution True Pareto Front 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



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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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Brno University of TechnologyBrnoCzech Republic

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