23rd International Conference on Multiple Criteria Decision Making MCDM 2015 - Bridging Disciplines
August 2nd–7th, 2015, Hamburg, Germany
|01.10.2015|
The submission deadline for the Special Issue of the Computers and Operations Research Journal on "Evolutionary Multiobjective Optimization" has been extended to October 15, 2015.
|24.08.2015|
Now the Book of Abstracts can be downloaded. Also a short program is available. Note that each document will be provided in a printed version at the conference.
|13.08.2015|
The photos of the scientific and the social program can be downloaded here.
|31.07.2015|
The Master Track Schedule (also provided in a printed version) and the Session Chair Instructions can be downloaded.
|09.07.2015|
The public transportation ticket will be sent to registered participants who have pre-paid the conference fee by 27th of July at the latest.
|08.07.2015|
The final timetable is online.
|04/2015|
Conference registration opens.
|04/2015|
Apply for free voucher codes for traveling to Hamburg with FlixBus.
|03/2015|
Update on the social program.
Carlos M. Fonseca
Carlos M. Fonseca is an Associate Professor at the Department of Informatics Engineering of the University of Coimbra, Portugal, and the Head of the Evolutionary and Complex Systems (ECOS) group of the Centre for Informatics and Systems of the University of Coimbra (CISUC). He graduated in Electronic and Telecommunications Engineering from the University of Aveiro, Portugal, in 1991, and obtained a Ph.D. in Automatic Control and Systems Engineering from the University of Sheffield, U.K., in 1996. He was a Research Associate with the Department of Automatic Control and Systems Engineering of the University of Sheffield from 1994 until 1997, and a Lecturer at the Department of Electronic Engineering and Informatics, Faculty of Science and Technology, University of Algarve, Faro, Portugal, from 1997 until October 2010, when he joined the University of Coimbra.
His research has been devoted mainly to evolutionary computation and multi-objective optimization. In the 1990's, he proposed MOGA, a "first-generation" multi-objective evolutionary algorithm with support for progressive preference articulation through goals and priorities, and began the development of the attainment-function approach to the experimental evaluation of stochastic multi-objective optimization algorithms. Since then, he has focused on the study of evolutionary algorithm dynamics, including representation and convergence aspects; further development of statistical methodologies for the experimental evaluation of multi-objective optimization algorithms, and of efficient algorithms to support them; and the development of new, computationally efficient, approaches to preference articulation in evolutionary multi-objective optimization. He has also contributed to several applications in the engineering and management domains.
Carlos Fonseca has authored or co-authored sixteen articles in peer-reviewed journals, over forty articles in refereed conference and workshop proceedings, and nine book chapters. He has collaborated with researchers at the Technical University of Darmstadt, Technical University of Dortmund, University of Koblenz-Landau, and University of Wuppertal in Germany, Leiden University in the Netherlands, Université Libre de Bruxelles (ULB) in Belgium, ETH Zurich in Switzerland, Indian Institute of Technology Kanpur (IITK) in India, and Federal University of Minas Gerais (UFMG), Federal Centre for Technological Education of Minas Gerais (CEFET-MG), and University of São Paulo (USP), in Brazil, among others. He has hosted and supervised five Ph.D. internship students and two post-docs on grants from Brazil.
He was a General co-Chair of the International Conference on Evolutionary Multi-Criterion Optimization (EMO) in 2003, 2009 and 2013, and a Technical co-Chair of the IEEE Congress on Evolutionary Computation (CEC) in 2000 and 2005. He is a member of the Evolutionary Multi-Criterion Optimization Steering Committee, and of the Portuguese Operations Research Association (APDIO).