AN OVERVIEW OF EVOLUTIONARY METHODS OF MULTI-CRITERIA OPTIMIZATION
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.
multi-criteria optimization; evolutionary optimization; genetic algorithms
Horn J., Nafpliotis N., Goldberg D.: A Niche Pareto Genetic Algorithm for Multiobjective Optimalization, IEEE 1994.
Kulczycki J.: Optymalizacja struktur sieci elektroenergetycznych, WNT 1990.
Michalewicz Z.: Algorytmy genetyczne + struktury danych = programy ewolucyjne, WNT 1999.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.