"We often come across computational optimization virtually in all branches of engineering and industry. Many engineering problems involve heuristic search and optimization, and, once discretized, may become combinatorial in nature, which gives rise to certain difficulties in terms of solution procedure. Some of these problems have enormous search spaces, are NP-hard and hence require heuristic solution techniques. Another difficulty is the lack of ability of classical solution techniques to determine appropriate optima of non-convex problems. Under these conditions, recent advances in computational optimization techniques have been shown to be advantageous and successful compared to classical approaches. This Volume presents some of the latest developments with a focus on the design of algorithms for computational optimization and their applications in practice. Through the chapters of this book, researchers and practitioners share their experience and newest methodologies with regard to intelligent optimization and provide various case studies of the application of intelligent optimization techniques in real-world applications.This book can serve as an excellent reference for researchers and graduate students in computer science, various engineering disciplines and the industry."--Publisher's website Front Matter....Pages - Intelligent Computational Optimization in Engineering: Techniques and Applications....Pages 1-24 Front Matter....Pages 25-25 Learning Automata in Control Planning Strategies....Pages 27-54 Optimization Strategies for Restricted Candidate Lists in Field Service Scheduling....Pages 55-83 Framework for Integrating Optimization and Heuristic Models for Solving Planning and Scheduling Problem in a Resin Manufacturing Plant....Pages 85-107 Evolutionary Algorithms in the Optimal Sizing of Analog Circuits....Pages 109-138 Front Matter....Pages 139-139 Application of Estimation of Distribution Algorithms for Nuclear Fuel Management....Pages 141-176 Optimal Control Systems with Reduced Parametric Sensitivity Based on Particle Swarm Optimization and Simulated Annealing....Pages 177-207 Comparison of Evolutionary and Swarm Intelligence Methods for History Matching and Uncertainty Quantification in Petroleum Reservoir Models....Pages 209-240 Optimization of Multiple Traveling Salesmen Problem by a Novel Representation Based Genetic Algorithm....Pages 241-269 Front Matter....Pages 271-271 Out-of-the-Box and Custom Implementation of Metaheuristics. A Case Study: The Vehicle Routing Problem with Stochastic Demand....Pages 273-295 Analogue Circuit Optimization through a Hybrid Approach....Pages 297-327 Evolutionary Inventory Control for Multi-Echelon Systems....Pages 329-356 Fuzzy Skyhook Surface Control Using Micro-Genetic Algorithm for Vehicle Suspension Ride Comfort....Pages 357-394 Back Matter....Pages - We often come across computational optimization virtually in all branches of engineering and industry.¡Many engineering problems involve heuristic search and optimization, and, once discretized, may become combinatorial in nature, which gives rise to certain difficulties in terms of solution procedure. Some of these problems have enormous search spaces, are NP-hard and hence require heuristic solution techniques. Another difficulty is the lack of ability of classical solution techniques to determine appropriate optima of non-convex problems. Under these conditions, recent advances in computational optimization techniques have been shown to be advantageous and successful compared to classical approaches. ¡ This Volume presents some of the latest developments with a focus on the design of algorithms for computational optimization and their applications in practice.¡Through the chapters of this book, researchers and practitioners share their experience and newest methodologies with regard to intelligent optimization and provide various case studies of the application of intelligent optimization techniques in real-world applications. This book can serve as an excellent reference for researchers and graduate students in computer science, various engineering disciplines and the industry We often come across computational optimization virtually in all branches of engineering and industry. Many engineering problems involve heuristic search and optimization, and, once discretized, may become combinatorial in nature, which gives rise to certain difficulties in terms of solution procedure. Some of these problems have enormous search spaces, are NP-hard and hence require heuristic solution techniques. Another difficulty is the lack of ability of classical solution techniques to determine appropriate optima of non-convex problems. Under these conditions, recent advances in computational optimization techniques have been shown to be advantageous and successful compared to classical approaches. This Volume presents some of the latest developments with a focus on the design of algorithms for computational optimization and their applications in practice. Through the chapters of this book, researchers and practitioners share their experience and newest methodologies with regard to intelligent optimization and provide various case studies of the application of intelligent optimization techniques in real-world applications. This book can serve as an excellent reference for researchers and graduate students in computer science, various engineering disciplines and the industry
