Swarm Intelligence and Evolutionary Computing

Traditional optimization methods are no longer adequate to solve complex real life problems, as most of them involve nonlinear, discontinuous, non- differentiable, nonconvex, multiobjective functions with mixed variables in their model formulation. Over the last few years, the use of nature inspired meta-heuristic algorithms for systems optimization has increased tremendously, and "swarm intelligence and evolutionary computing techniques" are rapidly emerging as powerful tools for solving practical problems. This book describes efficient computational techniques based on Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Differential Evolution (DE) principles for single and multiple criterion optimization; and hybrid soft-computing techniques such as PSO Neural Network (PSO-NN), Adaptive Network Fuzzy Inference System (ANFIS) for hydrologic forecasting and demonstrates their applications to case studies in reservoir systems operation. This book is intended for people who are willing to learn new technology to solve complex real life problems and especially useful to professional in water resources field.