Overview
- Provides practical and novel optimization techniques that can be adapted to a broad spectrum of applications ranging from Engineering to Finance
- Discusses theoretical studies that underpin some of the optimality conditions in nonlinear optimization
- Explores evolutionary methods such as Genetic Algorithm and Ant Colony and shows how they can be adapted for both discrete and continuous decision problems
Part of the book series: Asset Analytics (ASAN)
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Table of contents (20 chapters)
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Front Matter
Keywords
- Optimization Science
- Π Fraction-based Optimization
- Artificial Bee Colony Based Hyper-heuristic
- Artificial Physics Optimization
- Benchmark Function Generators
- Evolutionary Optimization
- Feature Analysis
- Feature Extraction
- Gravitational Search Algorithm
- Multistoried Building
- Large-scale Optimization Problems
- Long Wave Equations
- Multi-variant Evolutionary Synthesis
- Optimal Configuration Selection
- Optimality Conditions
- Robust Optimisation Algorithms
- Seismic Analysis
- Sine-Cosine Algorithm
- Spider Monkey Optimization
- Task Scheduling Algorithm
About this book
This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems. Many of these problems can be modeled as nonlinear optimization problems, but due to their complex nature, it is not always possible to solve them using conventional optimization theory. Accordingly, the book discusses the design and applications of non-conventional numerical optimization techniques, including the design of benchmark functions and the implementation of these techniques to solve real-world optimization problems.
The book’s twenty chapters examine various interesting research topics in this area, including: Pi fraction-based optimization of the Pantoja–Bretones–Martin (PBM) antenna benchmarks; benchmark function generators for single-objective robust optimization algorithms; convergence of gravitational search algorithms on linear and quadratic functions; and an algorithm for the multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes.
Delivering on its promise to explore real-world scenarios, the book also addresses the seismic analysis of a multi-story building with optimized damper properties; the application of constrained spider monkey optimization to solve portfolio optimization problems; the effect of upper body motion on a bipedal robot’s stability; an ant colony algorithm for routing alternate-fuel vehicles in multi-depot vehicle routing problems; enhanced fractal dimension-based feature extraction for thermal face recognition; and an artificial bee colony-based hyper-heuristic for the single machine order acceptance and scheduling problem.
The book will benefit not only researchers, but also organizations active in such varied fields as Aerospace, Automotive, Biotechnology, Consumer Packaged Goods, Electronics, Finance, Business & Banking, Oil, Gas & Geosciences, and Pharma, to name a few.
Editors and Affiliations
About the editors
Dr. Kusum Deep is a Professor at the Department of Mathematics, Indian Institute of Technology Roorkee. Her research interests include numerical optimization, nature inspired optimization, computational intelligence, genetic algorithms, parallel genetic algorithms, and parallel particle swarm optimization.
Dr. Madhu Jain is an Associate Professor at the Department of Mathematics, Indian Institute of Technology Roorkee. Her research interests include computer communications networks, performance prediction of wireless systems, mathematical modeling, and biomathematics.
Dr. Said Salhi is Director of the Centre for Logistics & Heuristic Optimization (CLHO) at Kent Business School, University of Kent, UK. Prior to his appointment at Kent in 2005, Said served at the University of Birmingham’s School of Mathematics for 15 years, where in the latter years he acted as Head of the Management Mathematics Group. He obtained his BSc in Mathematics at Algiers’s University, and his MSc and PhD in OR at Southampton (Institute of Mathematics) and Lancaster (School of Management), respectively. Dr. Said has edited 6 special journal issues, chaired the European Working Group in Location Analysis in 1996 and recently the International Symposium on Combinatorial Optimisation (CO2016) in Kent, 1–3 September 2016. He has published over 100 papers in academic journals.
Bibliographic Information
Book Title: Decision Science in Action
Book Subtitle: Theory and Applications of Modern Decision Analytic Optimisation
Editors: Kusum Deep, Madhu Jain, Said Salhi
Series Title: Asset Analytics
DOI: https://doi.org/10.1007/978-981-13-0860-4
Publisher: Springer Singapore
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2019
Hardcover ISBN: 978-981-13-0859-8Published: 22 September 2018
Softcover ISBN: 978-981-13-4520-3Published: 11 January 2019
eBook ISBN: 978-981-13-0860-4Published: 12 September 2018
Series ISSN: 2522-5162
Series E-ISSN: 2522-5170
Edition Number: 1
Number of Pages: VII, 276
Number of Illustrations: 25 b/w illustrations, 62 illustrations in colour
Topics: Operations Research/Decision Theory, Operations Research, Management Science, Statistics for Business, Management, Economics, Finance, Insurance