In recent decades, several multi-objective evolutionary algorithms have been successfully
applied to a wide variety of multi-objective optimization problems. Along the way, several …

Metaheuristics have yielded very promising results for the frequency assignment problem
(FAP). However, the results obtainable using currently published methods are far from ideal …

In recent decades, several multi-objective evolutionary algorithms have been successfully
applied to a wide variety of multi-objective optimization problems. Along the way, several …

Throughout the last years, optimization problems on a large number of variables, sometimes
over 1000, are becoming common. Thus, algorithms that can tackle them effectively, both in …

Multi-objectivization represents a current and promising research direction which has led to
the development of more competitive search mechanisms. This concept involves the …

Traffic congestion, and the consequent loss of time, money, quality of life, and higher
pollution, is currently one of the most important problems in cities, and several approaches …

Premature convergence is one of the most important recurrent drawbacks of Evolutionary
Algorithms and other metaheuristics. As a result, several methods to alleviate this problem …

One of the most commonly known weaknesses of Evolutionary Algorithms (eas) is the large
dependency between the values selected for their parameters and the results. Parameter …

A framework called ParHyFlex and its underlying principle are presented. ParHyFlex is
based on the sequential HyFlex framework and also supports the implementation of different …

Излагается гибридный метод идентификации структуры и параметров нечетких
систем, основанный на модели островов. Идентификация структуры выполняется …