Nature-Inspired Methods for Metaheuristics Optimization [[electronic resource] ] : Algorithms and Applications in Science and Engineering / / edited by Fouad Bennis, Rajib Kumar Bhattacharjya

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
• Edizione: 1st ed. 2020.
• Descrizione fisica: 1 online resource (XIII, 502 p. 252 illus., 110 illus. in color.)
• Disciplina: 006.38
• Soggetto topico: Operations research; Management science; Computational intelligence; Hydrology; Mechanics; Mechanics, Applied; Thermodynamics; Heat engineering; Heat transfer; Mass transfer; Industrial engineering; Production engineering; Operations Research, Management Science; Computational Intelligence; Hydrology/Water Resources; Theoretical and Applied Mechanics; Engineering Thermodynamics, Heat and Mass Transfer; Industrial and Production Engineering
• Persona (resp. second.): BennisFouad; BhattacharjyaRajib Kumar
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Part I. Algorithms: 1. Genetic algorithms: A mature bio-inspired optimization technique for difficult problems -- 2. Introduction to Genetic Algorithm with a Simple Analogy -- 3. Interactive genetic algorithm to collect user perceptions. Application to the design of stemmed glasses -- 4. Differential Evolution and its application in Identification of Virus Release Location in a Sewer Line -- 5. Artificial Bee Colony Algorithm and An Application to Software Defect Prediction -- 6. Firefly Algorithm and its Applications in Engineering Optimization -- 7. Introduction to Shuffled Frog Leaping Algorithm and its Sensitivity to the Parameters of the Algorithm -- 8. Groundwater Management using Coupled Analytic Element based Transient Groundwater Flow and Optimization Model -- 9. Investigation of Bacterial Foraging Algorithm applied for PV parameter estimation, Selective harmonic elimination in inverters and optimal power flow for stability -- 10. Application of artificial immune system in Optimal Design of Irrigation Canal -- 11. Biogeography Based Optimization for Water Pump Switching Problem -- 12. Introduction to Invasive Weed Optimization Method -- 13. Single-Level Production Planning in Petrochemical Industries using Novel Computational Intelligence Algorithms -- 14. A Multi-Agent platform to support knowledge based modelling in engineering Design -- Part II. Applications: 15. Synthesis of reference trajectories for humanoid robot supported by genetic algorithm -- 16. Linked Simulation Optimization Model for Evaluation of Optimal Bank Protection Measures -- 17. A GA Based Iterative Model for Identification of Unknown Groundwater Pollution Sources Considering Noisy Data -- 18. Efficiency of Binary Coded Genetic Algorithm in Stability Analysis of an Earthen Slope -- 19. Corridor allocation as a constrained optimization problem using a permutation-based multi-objective genetic algorithm -- 20. The constrained single-row facility layout problem with repairing mechanisms -- 21. Geometric size optimization of annular step fin array for heat transfer by natural convection -- 22. Optimal control of saltwater intrusion in coastal aquifers using analytical approximation based on density dependent flow correction -- 23. Dynamic Nonlinear Active Noise Control. A Multi-Objective Evolutionary Computing Approach -- 24. Scheduling of Jobs on Dissimilar Parallel Machine using Computational Intelligence Algorithms -- 25. Branch-and-Bound Method for Just-in-Time Optimization of Radar Search Patterns -- 26. Optimization of the GIS based DRASTIC model for Groundwater Vulnerability Assessment.
• Sommario/riassunto: This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.
• Titolo autorizzato: Nature-Inspired Methods for Metaheuristics Optimization
• ISBN: 3-030-26458-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910373906103321
• Lo trovi qui: Univ. Federico II
• Serie: Modeling and Optimization in Science and Technologies, . 2196-7326 ; ; 16