This approach provides a novel methodology for address-ing a well-known problem of Software Engineering, the prioritization of software requirements. The proposal combines the use of tools such as the Analytic Hierarchy Process (AHP), the Self-Organizing Maps (SOM) and al-so methods belonging to the...

This paper presents two proactive algorithms that act as meta-metaheuristic agents: they decide which metaheuristic will be used to solve a new problem. These meta-metaheuristic agents operate in the environment of iterative work on optimizing problems, with the goal of selecting good metaheuristics...

This paper formulates the 3D Stochastic Stowage Plan-ning (3D SSP) problem. The key objective of 3D SSP is to minimize the number of container movements and maximize the ship´s stability considering multiple scenar-ios. The binary formulation of this problem is described and an alternative formulation,...

In this paper, a review about the quality of the similarity measure and its applications in machine learning is presented. This measure is analyzed from the perspective of the granular computing. The granular computing allows analyzing the information at different levels of abstraction and from different...

In this work we present a new hybrid approach for solv-ing the clustering problem for geographic data, which is known to be NP-hard. Two metaheuristics that have prov-en efficiency in combinatory optimization problems have been chosen for the comparison: Simulated Annealing (SA) and Variable Neighborhood...