Foundations of Computational Intelligence Volume 3: Global Optimization (Studies in Computational Intelligence (203))

Annotation Global optimization is a branch of applied mathematics and numerical analysis that deals with the task of finding the absolutely best set of admissible conditions to satisfy certain criteria / objective function(s), formulated in mathematical terms. Global optimization includes nonlinear, stochastic and combinatorial programming, multiobjective programming, control, games, geometry, approximation, algorithms for parallel architectures and so on. Due to its wide usage and applications, it has gained the attention of researchers and practitioners from a plethora of scientific domains. Typical practical examples of global optimization applications include: Traveling salesman problem and electrical circuit design (minimize the path length); safety engineering (building and mechanical structures); mathematical problems (Kepler conjecture); Protein structure prediction (minimize the energy function) etc. Global Optimization algorithms may be categorized into several types: Deterministic (example: branch and bound methods), Stochastic optimization (example: simulated annealing). Heuristics and meta-heuristics (example: evolutionary algorithms) etc. Recently there has been a growing interest in combining global and local search strategies to solve more complicated optimization problems. This edited volume comprises 17 chapters, including several overview Chapters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of global optimization. Besides research articles and expository papers on theory and algorithms of global optimization, papers on numerical experiments and on real world applications were also encouraged. The book is divided into 2 main parts Front Matter....Pages - Front Matter....Pages 1-1 Genetic Algorithms for the Use in Combinatorial Problems....Pages 3-22 Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications....Pages 23-55 Global Optimization Using Harmony Search: Theoretical Foundations and Applications....Pages 57-73 Hybrid GRASP Heuristics....Pages 75-100 Particle Swarm Optimization: Performance Tuning and Empirical Analysis....Pages 101-128 Tabu Search to Solve Real-Life Combinatorial Optimization Problems: A Case of Study....Pages 129-151 Reformulations in Mathematical Programming: A Computational Approach....Pages 153-234 Graph-Based Local Elimination Algorithms in Discrete Optimization....Pages 235-266 Evolutionary Approach to Solving Non-stationary Dynamic Multi-Objective Problems....Pages 267-289 Turbulent Particle Swarm Optimization Using Fuzzy Parameter Tuning....Pages 291-312 Front Matter....Pages 313-313 An Evolutionary Approximation for the Coefficients of Decision Functions within a Support Vector Machine Learning Strategy....Pages 315-346 Evolutionary Computing in Statistical Data Analysis....Pages 347-386 Meta-heuristics for System Design Engineering....Pages 387-423 Transgenetic Algorithm: A New Endosymbiotic Approach for Evolutionary Algorithms....Pages 425-460 Multi-objective Team Forming Optimization for Integrated Product Development Projects....Pages 461-478 Genetic Algorithms for Task Scheduling Problem....Pages 479-507 PSO_Bounds: A New Hybridization Technique of PSO and EDAs....Pages 509-526 Back Matter....Pages - The positive response to the publication of Blanton's English translations of Euler's "Introduction to Analysis of the Infinite" confirmed the relevance of this 240 year old work and encouraged Blanton to translate Euler's "Foundations of Differential Calculus" as well. The current book constitutes just the first 9 out of 27 chapters. The remaining chapters will be published at a later time. With this new translation, Euler's thoughts will not only be more accessible but more widely enjoyed by the mathematical community.