Multi-objective Optimization

Abstract

Diversity problems are usually studied from a single-objective point of view. However, two or more diversity functions could present opposite or divergent behavior, which requires a multi-objective point of view. To illustrate this kind of problems, this chapter presents the study of the bi-objective diversity problem (BODP), which considers the MaxSum and the MaxMin as objective functions to simultaneously maximize. Six different multi-objective algorithms have been described, analyzing their results on six performance metrics using a subset of instances from the MDPLIB 2.0 library.

Publication
Discrete Diversity and Dispersion Maximization
J. Manuel Colmenar
J. Manuel Colmenar
Full Professor

My research interests are focused on metaheuristics applied to optimization problems. I have worked on different combinatorial optimization problems applying trajectorial algorithms such us GRASP or VNS. Besides, I am very interested in applications of Grammatical Evolution, specifically in model and prediction domain, as alternative to machine learning approaches.

Alberto Herrán González
Alberto Herrán González
Associate Professor
Raúl Martín Santamaría
Raúl Martín Santamaría
Phd in Artificial Intelligence

My research interests include…