Event Location: GHC 2109
Bio: Dr. Gideon Avigad has recently joined Vineland Research and Innovation Centre as Program
Leader – Robotics & Automation. He has been a tenure at the Mechanical Engineering Department,
Braude College of Engineering, Israel where he taught control and mechatronics related courses and led
many robotics R&D projects. In the last two years he was a visiting/adjunct professor at Western
University, where he had the opportunity to further expand his research collaborations across the
university, other Canadian universities and industry. His research is focused on multi-objective
optimization, especially as related to optimizing solutions to problems that involve uncertainties.

Abstract: Evolutionary Computation (EC) has become an important heuristic often used to search for
solutions to optimization problems. Utilizing EC for solving Multi-Objective Optimization Problems
(MOPs) has become a winning choice. Since the development of Multi-Objective Evolutionary
Algorithms (MOEAs) have been mainly used for evolving the Pareto front of the problem. The Pareto
front is a collection of points in objective space, each representing performances of an optimal solution.
In contrast, in Set-Based Design and Evolution (SBDE), a single solution is represented in the objective
space by a set of points. In such problems, the Pareto front is more of a layer rather than a clear cut
front. Naturally, when considering MOEAs to search for such solutions, they should be adapted to
enhance the evolution of solutions, which are represented by sets.

In the seminar, following a brief clarification of the Pareto front notion and a short explanation regarding
the search of solutions to MOPs by EC, several problems associated with SBDE will be discussed,
including multi-objective games, optimizing adaptability, transient response optimization and
mechanical cognitivization .