Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications [Paperback]

This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in applicationcontexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications.
Introduction and Overview:  Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications.- PART 1: Civil and Structural Engineering.- Harmony Search Algorithm for Structural Engineering Problems.- Teaching Learning Based Optimum Design of Transmission Tower Structures.- Modified Artificial Bee Colony Algorithm for Sizing Optimization of Truss Structures.- Electrostatic Discharge Algorithm for Optimum Design of Real Size Truss Structures.- Solving of Distinct Engineering Optimization Problems using Metaheuristic Algorithms.- The Design of Trapezoidal Corrugated Web Beams using Firefly Method.- Designing Fuzzy Controllers for Frame Structures Based on Ground Motion Prediction using Grasshopper Optimization Algorithm; A Case Study of Tabriz, Iran.- Optimization and lƒ$