This book presents an overview of several archiving strategies we have developed over the
last years dealing with approximations of the solution sets of multi-objective optimization …

The Graph Partitioning Problem (GPP) is a well-known NP-hard combinatorial problem that
involves the finding of a partition of vertexes that minimizes the number of cut edges while …

The proper management of diversity is essential to the success of Evolutionary Algorithms.
Specifically, methods that explicitly relate the amount of diversity maintained in the …

Menu planning is a complex task that involves finding a combination of menu items by taking
into account several kinds of features, such as nutritional and economical, among others. In …

Algorithms relating the amount of population's diversity to the elapsed period of execution
have yielded important improvements. Particularly, schemes with a gradual shift from …

This research establishes an identity between kinetic market models of econophysics and
evolutionary algorithms of computer science. The fusion between the two approaches …

The balance between exploration and exploitation is an important feature in Evolutionary
Algorithms (EA). The use of different operators permits to explore the search space and …

One of the issues that might affect the performance of Differential Evolution (DE) is
premature convergence. In such cases, and especially in long-term executions, due to the …

Population-based algorithms are flexible methods that can be effectively applied to complex
optimization problems. As part of their design, several aspects have to be taken into …

El problema del Particionado de Grafos (gpp—Graph Partitioning Problem) es un problema
NP-Difıcil cuyo objetivo es particionar los nodos de un grafo en k conjuntos de forma que se …