neo2018

The Attainment Function Approach to Performance Evaluation in Evolutionary Multiobjective Optimization

Instructors:

  • Dr. Carlos Fonseca

Abstract: 

Carlos M. Fonseca is an Associate Professor at the Department of Informatics Engineering of the University of Coimbra, Portugal, and a member 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. His research has been devoted mainly to evolutionary computation and multi-objective optimization, with a focus on computationally efficient approaches to preference articulation and experimental performance evaluation in evolutionary multi-objective optimization. He is the Scientific Representative of the Grant Holder of COST Action CA15140 – Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO), and the leader of a Working Group on Software in that Action. He has served as General, Technical or Track co-Chair of several major international conferences on evolutionary computation, and is a member of the Evolutionary Multi-Criterion Optimization and of the Parallel Problem Solving from Nature Steering Committees.