We incorporate them into an evolutionary algorithm, giving rise to the so-called Maximin-Clustering Multi-Objective Evolutionary Algorithm (MC-MOEA) approach.
Motivation. When designing multi-objective evolutionary al- gorithms (MOEAs), there are two main types of ap- proaches that are normally used as selection ...
Selection Operators Based on Maximin Fitness Function for Multi ...
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Abstract. We analyze here some properties of the maximin fitness func- tion, which has been used by several researchers, as an alternative to.
2016/03/01 · In this paper, we study three selection mechanisms based on the maximin fitness function and we propose another one.
含まれない: Operators Evolutionary Algorithms.
2016/03/01 · In this paper, we study three selection mechanisms based on the maximin fitness function and we propose another one.
In this paper, we study three selection mechanisms based on the maximin fitness function and we propose another one. These selection mechanisms give rise to ...
We analyze here some properties of the maximin fitness function, which has been used by several researchers, as an alternative to Pareto optimality, ...
We incorporate them into an evolutionary algorithm, giving rise to the so-called Maximin-Clustering Multi-Objective Evolutionary Algorithm (MC-MOEA) approach.
In this paper, we propose a new selection mechanism based on the maximin fitness function and a technique based on Euclidean distances between solutions to ...
The maximin fitness function can be used in multi-objective genetic algorithms to obtain a diverse set of non-dominated designs to address land-use and ...