When solving multiobjective optimization problems, preference-based evolutionary
multiobjective optimization (EMO) algorithms introduce preference information into an …

Interactive multiobjective optimization methods incorporate preferences from a human
decision maker in the optimization process iteratively. This allows the decision maker to …

The growth and expansion of tourism is a complex phenomenon and its study requires
multiple disciplines. When related to sustainability, the growth limits and carrying capacity of …

Counterfactual Analysis has shown to be a powerful tool in the burgeoning field of
Explainable Artificial Intelligence. In Supervised Classification, this means associating with …

Most interactive methods developed for solving multiobjective optimization problems
sequentially generate Pareto optimal or nondominated vectors and the decision maker must …

In this article, we propose a new evolutionary algorithm for multiobjective optimization called
Global WASF-GA (global weighting achievement scalarizing function genetic algorithm) …

This paper proposes a novel optimization approach for multi-scenario multi-objective robust
decision making, as well as an alternative way for scenario discovery and identifying …

Investment decision making may require the selection of the geographical areas where the
investments will be mainly done. A large number of factors could influence this decision …

Solving real-life data-driven multiobjective optimization problems involves many
complicated challenges. These challenges include preprocessing the data, modelling the …

Sustainability is nowadays a key factor to analyse the development of the societies.
Therefore, measuring sustainability is a main concern of the scientific community. The basic …