Abrão T. (ed.) Search Algorithms for Engineering Optimization

InTech, 2013, -292 p.Heuristic Search is an important sub-discipline of optimization theory and finds applications in a vast variety of fields, including life science and engineering. Over the years, search methods have made an increasing number of appearances in engineering systems, primarily because of the capability in providing effective near-optimum solutions with low-complexity, more cost-effective and less time consuming. Heuristic Search is a method that might not always find the best solution but is guaranteed to find a good solution in reasonable time, i.e., by sacrificing completeness it increases efficiency. Search methods have been useful in solving tough engineering-oriented problems that either could not be solved any other way or solutions take a very long time to be computed.
The primary goal of this book is to provide a variety of applications for search methods and techniques in different fields of electrical engineering. By organizing relevant results and applications, the book will serve as a useful resource for students, researchers and practitioners to further exploit the potential of search methods in solving hard non-polynomial optimization problems that arise in advanced engineering technologies, such as image and video processing issues, detection and resource allocation in telecommunication systems, security and harmonic reduction in power generation systems, as well as redundancy optimization problem and search-fuzzy learning mechanisms in industrial applications. To better explore those engineering- oriented search methods, this book is organized in four parts. In Part 1, three search optimization procedures applied to image and video processing are discussed. In Part 2, three specific hard optimization problems that arise in telecommunications systems are solved using guided search procedures: multiuser detection, power-rate allocation, anomaly detection and routing optical channel allocation problems are treaded deploying a collection of guided-search algorithms, such as Ant Colony, Particle Swarm, Genetic, Simulation Annealing, Tabu, Evolutionary Programming, Neighborhood Search and Hyper-Heuristic. Search methods applied to power systems and industrial processes are developed in Part 3: cognitive concepts and methods, such as fuzzy cognitive maps and adaptive fuzzy learning mechanisms are aggregated in order to efficiently model and solve optimization problems found in reliable power generation and industrial applications. Finally, the last chapter is devoted to conceptual and formal aspects of Grover-type quantum search, which constitutes Part 4.
It is our sincere hope that the book will help readers to further explore the potential of search methods in solving efficiently hard-complexity engineering optimization problems.Section 1 Image Reconstruction
Search Algorithm for Image Recognition Based on Learning Algorithm for Multivariate Data Analysis
Ant Algorithms for Adaptive Edge Detection
Content-Based Image Feature Description and Retrieving
Section 2 Telecommunication Applications
Multidimensional Optimization-Based Heuristics Applied to Wireless Communication Systems
Ant Colony Optimization for Resource Allocation and Anomaly Detection in Communication Networks
Optical Network Optimization Based on Particle Swarm Intelligence
Section 3 Power Systems and Industrial Processes Applications
An Adaptive Neuro-Fuzzy Strategy for a Wireless Coded Power Control in Doubly-Fed Induction Aerogenerators
Application of Harmony Search Algorithm in Power Engineering
Heuristic Search Applied to Fuzzy Cognitive Maps Learning
Optimal Allocation of Reliability in Series Parallel Production System
Section 4 Grover-Type Quantum Search
Geometry and Dynamics of a Quantum Search Algorithm for an Ordered Tuple of Multi-Qubits