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Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications

Medium: Buch
ISBN: 978-981-336-772-2
Verlag: Springer Nature Singapore
Erscheinungstermin: 01.04.2021
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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.

Produkteigenschaften

  • Artikelnummer: 9789813367722
  • Medium: Buch
  • ISBN: 978-981-336-772-2
  • Verlag: Springer Nature Singapore
  • Erscheinungstermin: 01.04.2021
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2021
  • Serie: Springer Tracts in Nature-Inspired Computing
  • Produktform: Gebunden
  • Gewicht: 805 g
  • Seiten: 404
  • Format (B x H x T): 160 x 241 x 29 mm
  • Ausgabetyp: Kein, Unbekannt

Themen

Autoren/Hrsg.

Herausgeber

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 Artificial Neural Network Models for Reinforced Concrete Members.- Statistical Investigation of the Robustness for the Optimization Algorithms.- Optimum Design of Beams with Varying Cross-Section by Using Application Interface.- Metaheuristic-based Structural Control Methods and Comparison of Applications.- Evolutionary Structural Optimization – A Trial Review.- An Extensive Review of Charged System Search Algorithm for Engineering Optimization Applications.- PART 2: Electrical and Electronics, Computer, and Communication Engineering.- Artificial Bee Colony Algorithm and Its Application to Content Filtering in Digital Communication.- Multi-objective Design of Multilayer Microwave Dielectric Filters using Artificial Bee Colony Algorithm.- Multi-objective Sparse Signal Reconstruction in Compressed Sensing.- Optimal Allocation of Flexible Alternative Current Transmission Systems: An Application of Particle Swarm Optimization.