Created by W.Langdon from gp-bibliography.bib Revision:1.7177
The first part is a heuristic study devoted to constraint handling in evolutionary computation. It presents an extensive review of previous constraint handling methods in the literature and their limitations. Two solutions are then proposed. The first idea is to improve genetic operator exploration capacity for constrained optimisation problems. The logarithmic mutation operator is conceived to explore both locally and globally the search space.
The second solution introduces the original Adaptive Segregational Constraint Handling Evolutionary Algorithm (ASCHEA), the main idea of which is to maintain population diversity. In order to achieve this goal, three main ingredients are used: An original adaptive penalty method, a constraint-driven recombination, and a segregation selection that distinguishes between feasible and infeasible individuals to enhance the chances of survival of the feasible ones. Moreover, a niching method with an adaptive radius is added to ASCHEA in order to handle multimodal functions.
Finally, to complete the ASCHEA system, a new equality constraint handling strategy is introduced, that reduces progressively the feasible domain in order to approach the actual null-measured domain as close as possible at the end of the evolution.
The second part is a case study tackling a real-world problem. The goal is to design the 2-dimensional profile of an optical lens (phase plate) in order to control focal-plane irradiance of some laser beam. The aim is to design the phase plate such that a small circular target on the focal plane is uniformly illuminated without energy loss.",
Genetic Programming entries for Sana Ben Hamida