José Antonio Lozano
University of the Basque Country, Spain
The essence of combinatorial optimization problems
The goal of this talk is to provide new views on combinatorial optimization problems. Particularly we consider two different scenarios which produce different rich information about the problems. In a first scenario we consider instances of combinatorial optimization problems as ranking of the elements of the search space. This allows us to compute those instances that are in the intersection between different combinatorial optimization problems. In a second scenario we use the Fourier transform. After calculating the Fourier coefficients of several problems we manage to discover their intrinsic dimensionalities, i.e. the minimum number of parameters required to define an instance of the problem.Furthermore, the Fourier coefficients equip us with the possibility to exactly compute the dimension of the intersection between different problems. This can give the base for transferring algorithms designed for one problem to a different problem.
Jose A. Lozano received his M.Sc. degree in mathematics and PhD in computer science from the University of the Basque Country UPV/EHU, in Spain, in 1992 and 1998 respectively. He has been a full professor at the University of the Basque since 2008 where he leads the Intelligent Systems Group. Since January 2019 he is the scientific director of the Basque Center for Applied Mathematics (Spain). Prof. Lozano has authored more than 110 ISI journal papers, some of them have become highly cited papers. His current research interests include combinatorial optimization, machine learning and its synergies with optimization in general and supervised classification, time series analysis and Bayesian inference in particular. Prof. Lozano has served on the organizing and program committee of over 60 international conferences being the general chair of IEEE Congress on Evolutionary Computation (IEEE CEC 2017) and the editor-in-chief of the Genetic and Evolutionary Computation Conference (GECCO 2020). He also serves as Associate Editor of top journals such as IEEE Trans. on Evolutionary Computation, Evolutionary Computation and IEEE Trans. on Neural Network and Learning Systems, to name but a few.
University degli Studi di Modena e Reggio Emilia, Italy
Roberto Serra graduated in Physics at the University of Bologna, where he was awarded the Guglielmo Marconi prize as the best graduate of his academic year. He later performed research activities for more than 20 years in different industrial groups (including the multinational groups Eni and Montedison) where he led various research groups; he served as director of the Montedison Environmental Research Centre for almost 10 years (1995-2004).In 2004 he moved to academia and became full professor of Complex Systems at the University of Modena and Reggio Emilia. He is also a Fellow and a Member of the Science Board of the European Centre for Living Technologies (an international research organization in Venice) and a Fellow of the Institute for Advanced Study of the University of Amsterdam. Roberto Serra has also been president of AI*IA (Associazione Italiana per l’ Intelligenza Artificiale) and chairman of the Science Board of the European Centre for Living Technologies. His research interests concern several aspects of the dynamics of complex systems, paying particular attention to biological systems. The most relevant recent works concern models of genetic networks and of protocells, and methods based on information theory to identify relevant sets of integrated variables in complex systems.