AN OVERVIEW OF EVOLUTIONARY METHODS OF MULTI-CRITERIA OPTIMIZATION


Abstract

Since the mid-eighties we can see the development of methods that are based on a new method of creating dominated solutions. They lead to designate the ratings Pareto front mimicking the mechanisms created in the world of micro and macro-nature. Currently, the existing optimization methods can include: genetic algorithms, evolutionary algorithms using artificial immune systems, swarm and formic algorithms. The article presents few selected evolutionary optimization methods, including evolutionary algorithm, formic and swarm algorithms, and NSGA. The article also describes how the different algorithms work and their exemplary application.


Keywords

multi-criteria optimization; evolutionary optimization; genetic algorithms

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Published : 2014-12-09


Gryniewicz-Jaworska, M. (2014). AN OVERVIEW OF EVOLUTIONARY METHODS OF MULTI-CRITERIA OPTIMIZATION. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 4(4), 32-34. https://doi.org/10.5604/20830157.1130178

Michalina Gryniewicz-Jaworska  michalina.gryniewicz.jaworska@vp.pl
Lublin University of Technology, Faculty of Electrical Engineering and Computer Science, Institute of Computer Science  Poland