Constraint-Handling in Evolutionary Optimization [Hardcover]

This book is the result of a special session on constraint-handling techniques used in evolutionary algorithms within the Congress on Evolutionary Computation (CEC) in 2007. It presents recent research in constraint-handling in evolutionary optimization.

Continuous Constrained Optimization with Dynamic Tolerance Using the COPSO Algorithm.- Boundary Search for Constrained Numerical Optimization Problems.- Solving Difficult Constrained Optimization Problems by the ? Constrained Differential Evolution with Gradient-Based Mutation.- Constrained Real-Parameter Optimization with ? -Self-Adaptive Differential Evolution.- Self-adaptive and Deterministic Parameter Control in Differential Evolution for Constrained Optimization.- An Adaptive Penalty Function for Handling Constraint in Multi-objective Evolutionary Optimization.- Infeasibility Driven Evolutionary Algorithm for Constrained Optimization.- On GA-AIS Hybrids for Constrained Optimization Problems in Engineering.- Constrained Optimization Based on Quadratic Approximations in Genetic Algorithms.- Constraint-Handling in Evolutionary Aerodynamic Design.- Handling Constraints in Global Optimization Using Artificial Immune Systems: A Survey.

An efficient and adequate constraint-handling technique is a key element in the design of competitive evolutionary algorithms to solve complex optimization problems. This edited book presents a collection of recent advances in nature-inspired techniques for constrained numerical optimization. The book covers six main topics: swarm-intelligence-based approaches, studies in differential evolution, evolutionary multiobjective constrained optimization, hybrid approaches, real-world applications and the recent use of the artificial immune system in constrained optimization. Within the chapters, the reader will find different studies about specialized subjects, such as: special mechanisms to focus the search on the boundaries of the feasible regionlc¿