Prof. Juergen Branke
Juergen Branke is Professor of Operational Research and Systems at Warwick Business School, University of Warwick, UK. He has been an active researcher in the field of Evolutionary Computation for over 20 years, has published over 170 papers in peer-reviewed journals and conferences, resulting in an H-Index of 52 (Google Scholar). His main research interests include optimization under uncertainty, simulation-based optimization and multi-objective optimization. Jürgen is Area Editor for the Journal of Heuristics and the Journal on Multi-Criteria Decision Analysis, and Associate Editor for the Evolutionary Computation Journal and IEEE Transactions on Evolutionary Computation.
Title of the talk: Preference learning in multi-objective optimisation and decision making
Abstract:
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Prof. Alessio Ishizaka
Alessio Ishizaka is Full Professor in Decision Analysis, research lead and Deputy Director of the Centre of Operations Research and Logistics (CORL) at the Portsmouth Business School of the University of Portsmouth. He received his PhD from the University of Basel (Switzerland). He worked successively for the University of Exeter (UK), University of York (UK) and Audencia Grande Ecole de Management Nantes (France). He has been visiting professor at the Università del Sannio, Politecnico di Torino, Università degli Studi di Trento, INSA Strasbourg, Université de Lorraine, Universität Mannheim, Università degli Studi di Modena e Reggio Emilia, Universität der Bundeswehr Hamburg, Université d’Aix-Marseille, Università degli Studi di Torino, Università degli Studi della Tuscia and Università degli Studi di Padova. His research is in the area of decision analysis, where he has published more than 50 papers. He is regularly involved in large European funded projects. He has been the chair, co-organiser and guest speaker of several conferences on this topic. Alongside his academic activities, he acts as a consultant for companies in helping them to take better decisions. He has written the key textbook Multicriteria Decision Analysis: methods and software.
Title of the talk: Multi-criteria sorting methods for AHP
Abstract: Six problem formulations exist in multi-criteria decision analysis (MCDA): choice, sorting, ranking, description, elimination and design problems. The Analytic Hierachy Process (AHP) is a useful and widespread method for solving choice and ranking problems. However, it is not adapted for sorting problems. Moreover, another practical limitation of AHP is that a high number of alternatives imply a large number of comparisons.
The first part of the talk presents AHPSort I, a new variant of the AHP, used for the sorting of alternatives into predefined ordered categories. Furthermore, AHPSort I requires far less comparisons than AHP, which facilitates decision making within large scale problems. In the second part of the talk, AHPSort II will be introduced, which requires far less comparisons. Moreover the number of pairwise comparisons does not depend on the number of alternatives, therefore it is suitable for very large problems.
AHPSort I will be illustrated with a supplier selection problem. AHPSort II will be illustrated with a risk assessment problem.
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Dr. David Walker
Dr David Walker is a Lecturer in Computer Science at the University of Plymouth. He has a PhD in Computer Science from the University of Exeter, where he conducted work on the visualisation of the mutually non-dominating sets generated by many-objective evolutionary algorithms. During his postdoctoral work he conducted research on the development of novel hyper-heuristics and interactive methods for solving optimisation problems. He joined the School of Computing, Electronics and Mathematics at the University of Plymouth in 2018, and is a member of both the Centre for Robotic and Neural Systems and Big Data Group. His research focuses on improving user understanding of nature-inspired algorithms using visualisation techniques, multi-criteria decision making, and incorporating humans as components of nature-inspired approaches using interactive evolution. He has organised a GECCO workshop on visualisation for the last seven years, and is active in reviewing for a range of journals.
Title of the talk: Visualisation in Many-objective Optimisation
Abstract: As algorithms capable of optimising many-objective problems mature, the visualisation of many-objective solution sets remains an important topic within the domain of evolutionary computation. This talk will survey some of the approaches taken to address this problem, demonstrating techniques that can be used to visualise solution sets comprising a large number of conflicting objectives. Looking beyond the standard use-case of allowing a decision maker to select a solution to implement, the talk will consider other ways in which many-objective visualisations can provide important information to evolutionary algorithm users, and addresses future directions of research.