SR

PROGRAMME

 

INVITED SPEAKERS

Salvatore Corrente

Department of Economics and Business, University of Catania

Interactive evolutionary multiobjective optimization guided by preference information

In multiobjective optimization one aims to simultaneously optimize a certain number of objective functions possibly under one or more constraints. However, since objectives are conflicting so that maximizing one of them implies that some others are reduced, there is not any solution that optimizes simultaneously all of them. Instead, a set of Pareto optimal solutions exists, containing solutions for which it is not possible to improve one objective without deteriorating someone other. In recent years evolutionary algorithms have been applied to multiobjective optimization problems to find a good approximation of the Pareto front. However, finding the whole set of Pareto optimal solutions, as well as some approximation, does not solve the optimization problem since one or some of these solutions, being the most preferred for the user, have to be discovered. Interactive evolutionary multiobjective optimization methods aim, therefore, to address the search to the most interesting part of the Pareto front by considering some preferences provided by the user during the procedure. In this talk we shall present two interactive evolutionary multiobjective optimization methods being NEMOIICh and XIMEA-DRSA. Both take into account the preferences expressed by the user during the optimization procedure. On the one hand, NEMOIICh tries to discover solutions that are the most preferred for at least one value function, formulated in terms of Choquet integral, compatible with the preference information provided by the user, while, on the other hand, XIMEA-DRSA guides the evolutionary optimization towards the most preferred part of the Pareto front using “if …, then…” decision rules induced from the preferences expressed by the user.

Salvatore Corrente is an Associate Professor for the SSD SECS-S/06 mathematical methods of economics, finance and actuarial science. His current teaching activity includes the unit General Mathematics (Bachelor of Economics - undergraduate) and the unit Decision Support Systems for the Territorial Planning (Master's degree in Economics and Management of the Territory and Tourism - postgraduate), both at the Department of Economics and Business of the University of Catania. He is a member of the scientific board of the Ph.D. in Economics, Management and Decision Making at the University of Catania. The research activity of Salvatore Corrente is mainly related to decision theory and, in particular, to Multicriteria Decision Aiding. For his research activity, he has obtained the Bernard Roy award 2020 from the European Working Group on Multicriteria Decision Aiding “As the highest recognition of the EWG-MCDA conferred on a young researcher for an outstanding contribution to the methodology and applications of Multiple Criteria Decision Aiding”. Moreover, he has been visiting professor at the University of Portsmouth from May 2nd to May 27th, 2017, under the Isambard Kingdom Brunel Fellowship Scheme. He has published 39 scientific papers in prestigious peer-reviewed journals such as European Journal of Operational Research, OMEGA, Computers & Operations Research, Annals of Operations Research, Decision Support Systems and Knowledge-Based Systems. He has also published five book chapters. According to Google Scholar, he has received 1850 citations and his h-index is 23. For Scopus, his citations are 1210 and his h-index is 20. Salvatore Corrente is Associate Editor for OMEGA: The International Journal of Management Science (IF 7.084), and he has reviewed more than 300 papers for many prestigious international journals such as the European Journal of Operational Research, OMEGA, Annals of Operations Research, Decision Support Systems, Knowledge-Based Systems and Computers & Operations Research. For many years he has co-organized streams on Multiple Criteria Decision Analysis at the EURO Conference on Operational Research and he has co-organized sessions on Multiple Criteria Decision Aiding at the annual AMASES conference, which is the Italian prominent conference for his scientific sector.

Miłosz Kadziński

Poznań University of Technology, Institute of Computing Science, Poland

Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system

The aim of the talk is to present a new methodology to lead the selection of Multiple Criteria Decision Analysis (MCDA) methods. It is implemented in the Multiple Criteria Decision Analysis Methods Selection Software (MCDA-MSS), a decision support system that helps analysts answer a recurring question in decision science: “Which is the most suitable Multiple Criteria Decision Analysis method (or a subset of MCDA methods) that should be used for a given Decision-Making Problem (DMP)?”. The MCDA-MSS provides guidance to lead decision-making processes and choose among an extensive collection (>200) of MCDA methods. These are assessed according to an original comprehensive set of problem characteristics. The accounted features concern problem formulation, preference elicitation and types of preference information, desired features of a preference model, and construction of the decision recommendation. The applicability of the MCDA-MSS has been tested on several case studies. The MCDA-MSS includes the capabilities of (i) covering from very simple to very complex DMPs, (ii) offering recommendations for DMPs that do not match any method from the collection, (iii) helping analysts prioritize efforts for reducing gaps in the description of the DMPs, and (iv) unveiling methodological mistakes that occur in the selection of the methods. A community-wide initiative involving experts in MCDA methodology, analysts using these methods, and decision-makers receiving decision recommendations will contribute to the expansion of the MCDA-MSS.

Dr hab. inž. Miłosz Kadziński - associate professor at the Institute of Computer Science of the Poznań University of Technology. In his research he deals with computer-aided decisions, an important stream of operations research. The original decision support methodology developed by him is based on the processing of incomplete and imprecise data about preferences into conclusions useful in solving multi-criteria decision problems. This methodology creatively combines artificial intelligence and decision theory with mathematical programming and computer simulations. The preference modeling algorithms proposed by him allow for the inclusion of various forms of holistic decision examples in the decision-making process, and the developed methods of resistance analysis allow for the development of recommendations with various levels of certainty. He is also the author of algorithms combining various scientific specialties, which enrich the traditionally understood decision support with aspects typical of machine learning, evolutionary multi-criteria optimization, efficiency analysis and border data analysis as well as group decisions and negotiations.

He published the results of his research in over 70 articles in leading journals from the Journal Citation Reports list in the category of operations research or computer science with artificial intelligence (including Omega, European Journal of Operational Research, Computers & Operations Research, Decision Support Systems, Information Sciences, Machine Learning). He cooperates with over a dozen leading European research centers in the development of decision support methods (including University of Catania, Erasmus University Rotterdam, University of Lisbon, Universitat Pompeu Fabra) and their applications in real decision-making problems (e.g. ETH Zurich, London School of Economics, University of Southern Denmark, TU Delft, University of Perugia). The main areas of these applications are transport, logistics, medicine, nanotechnology, environmental protection, spatial planning, construction, education and risk analysis.

Manager of research projects financed by the National Science Center (Sonata program) and the Ministry of Science and Higher Education (Iuventus Plus program). Vice-president of the international Decision Deck consortium, which brings together leading scientists in the development of open software for decision support. Member of the committee coordinating the activities of the European Working Group at EURO on multi-criteria decision support. One of the main organizers of EURO 2016 - the largest European conference on operational research.

The innovation and comprehensiveness of his achievements have resulted in the award of prestigious awards by international scientific associations on multi-criteria decision support (Multiple Criteria Decision Making Doctoral Dissertation Award) and operational research (EURO Doctoral Dissertation Award - top 3 and MCDM Junior Researcher Best Paper Award 2018 and 2019). Honored as the best reviewer by the European Journal of Operational Research in 2012-19, Group Decision and Negotiation in 2017. and Omega in 2017. Laureate of awards from the Foundation for Polish Science (START scholarship in 2013-14), Prime Minister of the Republic of Poland (scientific award in 2018), Ministry of Science and Higher Education (scientific awards in 2013 and 2018 and a scholarship for outstanding young scientists in 2013-16) and the Polish Academy of Sciences (the award of the O / PAN in Poznań for the best research in the field of technical sciences in 2013 and the award of the 4th Department of Technical Sciences in 2016)