Generating Customize Landscapes in Permutation-based Combinatorial Optimization Problems¶
Jose A. Lozano
Professor
Department of Computer Science and Artificial Intelligence University of the Basque Country, Spain
Abstract: Designing customize optimization problem instances is a key issue in optimization. They can be used to evaluate new algorithms proposals, to compare several optimization algorithms, or to evaluate algorithms that estimate the number of local optima of an instance. In this sense several proposals have given in the field of evolutionary computation for continuous optimization problems. However these proposals have not been extended to the combinatorial optimization arena. In this presentation we provide a method to generate customize landscapes in permutation-based combinatorial optimization problems. Based on a probabilistic model for permutations called the Mallows model we generate instances with a given number of local optima and with specific characteristics in relation with the basin of attraction of the local optima and global optima.
Bio: Jose A. Lozano received B.S. degrees in Mathematics and Computer Science and a Ph.D. degree in computer science from the University of the Basque Country, Spain, in 1991,1992, and 1998 respectively. Since 2008, he has been a Professor of Computer Science at the University of the Basque Country where he leads the Intelligent System Group. He has edited three books and has published over 60 refereed journal papers. His main research interests are evolutionary computation, machine learning, probabilistic modeling, and bioinformatics. He has been awared several best paper prizes in conferences and his publications have received more than 2500 citations. Prof. Lozano is an Associate Editor of IEEE Trans.on Evolutionary Computation and member of the editorial board of Evolutionary Computation, Soft Computing, Applied Intelligence and Neural Computing and Applications Journals.