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Soft Computing

, Volume 22, Issue 24, pp 8273–8288 | Cite as

Multi-objective imperialistic competitive algorithm with multiple non-dominated sets for the solution of global optimization problems

  • Zhavat Sherinov
  • Ahmet Ünveren
Methodologies and Application
  • 130 Downloads

Abstract

In this paper, we propose a multi-objective imperialistic competitive algorithm (MOICA) for solving global multi-objective optimization problems. The MOICA is a modified and improved multi-objective version of the single-objective imperialistic competitive algorithm previously proposed by Atashpaz-Gargari and Lucas (IEEE Congr Evolut Comput 7:4661–4666. doi: 10.1109/CEC.2007.4425083, 2007). The presented algorithm utilizes the metaphor of imperialism to solve optimization problems. Accordingly, the individuals in a population are referred to as countries, of which there are two types—colonies and imperialists. The MOICA incorporates competition between empires and their colonies for the solution of multi-objective problems. To this end, it employs several non-dominated solution sets, whereby each set is referred to as a local non-dominated solution (LNDS) set. All imperialists in an empire are considered non-dominated solutions, whereas all colonies are considered dominated solutions. In addition to LNDS sets, there is one global non-dominated solution (GNDS) set, which is created from the LNDS sets of all empires. There are two primary operators in the proposed algorithm, i.e., assimilation and revolution, which use the GNDS and LNDS sets, respectively. The significance of this study lies in a notable feature of the proposed algorithm, which is that no special parameter is used for diversity preservation. This enables the algorithm to prevent extra computation to maintain the spread of solutions. Simulations and experimental results on multi-objective benchmark problems show that the MOICA is more efficient compared to a few existing major multi-objective optimization algorithms because it produces better results for several test problems.

Keywords

Multi-objective metaheuristics Imperialistic competitive algorithm Multiple non-dominated sets Global optimization 

Notes

Acknowledgements

This study was funded by Eastern Mediterranean University (02).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Computer Engineering DepartmentEastern Mediterranean UniversityMağusa, Mersin 10Turkey

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