Metaheuristics For Portfolio Optimization

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Metaheuristic Approaches to Portfolio Optimization

Ray, Jhuma,Mukherjee, Anirban,Dey, Sadhan Kumar,Klepac, Goran
Metaheuristic Approaches to Portfolio Optimization Book PDF

Author : Ray, Jhuma,Mukherjee, Anirban,Dey, Sadhan Kumar,Klepac, Goran
Publisher : IGI Global
Page : 263 pages
File Size : 50,6 Mb
Release : 2019-06-22
Category : Business & Economics
ISBN : 9781522581048

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Metaheuristic Approaches to Portfolio Optimization by Ray, Jhuma,Mukherjee, Anirban,Dey, Sadhan Kumar,Klepac, Goran Pdf

Control of an impartial balance between risks and returns has become important for investors, and having a combination of financial instruments within a portfolio is an advantage. Portfolio management has thus become very important for reaching a resolution in high-risk investment opportunities and addressing the risk-reward tradeoff by maximizing returns and minimizing risks within a given investment period for a variety of assets. Metaheuristic Approaches to Portfolio Optimization is an essential reference source that examines the proper selection of financial instruments in a financial portfolio management scenario in terms of metaheuristic approaches. It also explores common measures used for the evaluation of risks/returns of portfolios in real-life situations. Featuring research on topics such as closed-end funds, asset allocation, and risk-return paradigm, this book is ideally designed for investors, financial professionals, money managers, accountants, students, professionals, and researchers.

Metaheuristics for Portfolio Optimization

G. A. Vijayalakshmi Pai
Metaheuristics for Portfolio Optimization Book PDF

Author : G. A. Vijayalakshmi Pai
Publisher : John Wiley & Sons
Page : 316 pages
File Size : 45,8 Mb
Release : 2017-12-27
Category : Computers
ISBN : 9781119482796

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Metaheuristics for Portfolio Optimization by G. A. Vijayalakshmi Pai Pdf

The book is a monograph in the cross disciplinary area of Computational Intelligence in Finance and elucidates a collection of practical and strategic Portfolio Optimization models in Finance, that employ Metaheuristics for their effective solutions and demonstrates the results using MATLAB implementations, over live portfolios invested across global stock universes. The book has been structured in such a way that, even novices in finance or metaheuristics should be able to comprehend and work on the hybrid models discussed in the book.

Metaheuristics for Portfolio Optimization

G. A. Vijayalakshmi Pai
Metaheuristics for Portfolio Optimization Book PDF

Author : G. A. Vijayalakshmi Pai
Publisher : John Wiley & Sons
Page : 316 pages
File Size : 54,5 Mb
Release : 2017-12-27
Category : Computers
ISBN : 9781119482789

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Metaheuristics for Portfolio Optimization by G. A. Vijayalakshmi Pai Pdf

The book is a monograph in the cross disciplinary area of Computational Intelligence in Finance and elucidates a collection of practical and strategic Portfolio Optimization models in Finance, that employ Metaheuristics for their effective solutions and demonstrates the results using MATLAB implementations, over live portfolios invested across global stock universes. The book has been structured in such a way that, even novices in finance or metaheuristics should be able to comprehend and work on the hybrid models discussed in the book.

Advances in Swarm Intelligence

Ying Tan,Hideyuki Takagi,Yuhui Shi,Ben Niu
Advances in Swarm Intelligence Book PDF

Author : Ying Tan,Hideyuki Takagi,Yuhui Shi,Ben Niu
Publisher : Springer
Page : 648 pages
File Size : 52,6 Mb
Release : 2017-07-18
Category : Computers
ISBN : 9783319618333

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Advances in Swarm Intelligence by Ying Tan,Hideyuki Takagi,Yuhui Shi,Ben Niu Pdf

The two-volume set of LNCS 10385 and 10386, constitutes the proceedings of the 8th International Conference on Advances in Swarm Intelligence, ICSI 2017, held in Fukuoka, Japan, in July/August 2017. The total of 133 papers presented in these volumes was carefully reviewed and selected from 267 submissions. The paper were organized in topical sections as follows: Part I: theories and models of swarm intelligence; novel swarm-based optimization algorithms; particle swarm optimization; applications of particle swarm optimization; ant colony optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithm; brain storm optimization algorithm; cuckoo searh; and firefly algorithm. Part II: multi-objective optimization; portfolio optimization; community detection; multi-agent systems and swarm robotics; hybrid optimization algorithms and applications; fuzzy and swarm approach; clustering and forecast; classification and detection; planning and routing problems; dialog system applications; robotic control; and other applications.

An Introduction to Metaheuristics for Optimization

Bastien Chopard,Marco Tomassini
An Introduction to Metaheuristics for Optimization Book PDF

Author : Bastien Chopard,Marco Tomassini
Publisher : Springer
Page : 226 pages
File Size : 40,9 Mb
Release : 2018-11-02
Category : Computers
ISBN : 9783319930732

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An Introduction to Metaheuristics for Optimization by Bastien Chopard,Marco Tomassini Pdf

The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.

Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms

Management Association, Information Resources
Research Anthology on Multi Industry Uses of Genetic Programming and Algorithms Book PDF

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 1534 pages
File Size : 51,9 Mb
Release : 2020-12-05
Category : Computers
ISBN : 9781799880998

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Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms by Management Association, Information Resources Pdf

Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.

Search and Optimization by Metaheuristics

Ke-Lin Du,M. N. S. Swamy
Search and Optimization by Metaheuristics Book PDF

Author : Ke-Lin Du,M. N. S. Swamy
Publisher : Birkhäuser
Page : 434 pages
File Size : 55,9 Mb
Release : 2016-07-20
Category : Computers
ISBN : 9783319411927

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Search and Optimization by Metaheuristics by Ke-Lin Du,M. N. S. Swamy Pdf

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

Nature-Inspired Methods for Metaheuristics Optimization

Fouad Bennis,Rajib Kumar Bhattacharjya
Nature Inspired Methods for Metaheuristics Optimization Book PDF

Author : Fouad Bennis,Rajib Kumar Bhattacharjya
Publisher : Springer Nature
Page : 503 pages
File Size : 41,5 Mb
Release : 2020-01-17
Category : Business & Economics
ISBN : 9783030264581

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Nature-Inspired Methods for Metaheuristics Optimization by Fouad Bennis,Rajib Kumar Bhattacharjya Pdf

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.

Advances in Swarm Intelligence

Ying Tan,Yuhui Shi,KAY CHEN TAN
Advances in Swarm Intelligence Book PDF

Author : Ying Tan,Yuhui Shi,KAY CHEN TAN
Publisher : Springer Science & Business Media
Page : 771 pages
File Size : 51,6 Mb
Release : 2010-06
Category : Computers
ISBN : 9783642134944

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Advances in Swarm Intelligence by Ying Tan,Yuhui Shi,KAY CHEN TAN Pdf

The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available. The scope of LNCS, including its subseries LNAI and LNBI, spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes More recently, several color-cover sublines have been added featuring, beyond a collection of papers, various added-value components; these sublines include In paallel to the printed book, each new volume is published electronically in LNCS Online.

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

Modestus O. Okwu,Lagouge K. Tartibu
Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications Book PDF

Author : Modestus O. Okwu,Lagouge K. Tartibu
Publisher : Springer Nature
Page : 192 pages
File Size : 46,8 Mb
Release : 2020-11-13
Category : Technology & Engineering
ISBN : 9783030611118

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Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications by Modestus O. Okwu,Lagouge K. Tartibu Pdf

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Metaheuristics for Hard Optimization

Johann Dréo,Alain Pétrowski,Patrick Siarry,Eric Taillard
Metaheuristics for Hard Optimization Book PDF

Author : Johann Dréo,Alain Pétrowski,Patrick Siarry,Eric Taillard
Publisher : Springer Science & Business Media
Page : 372 pages
File Size : 53,9 Mb
Release : 2006-01-16
Category : Mathematics
ISBN : 9783540309666

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Metaheuristics for Hard Optimization by Johann Dréo,Alain Pétrowski,Patrick Siarry,Eric Taillard Pdf

Contains case studies from engineering and operations research Includes commented literature for each chapter

Hybrid Metaheuristics

Christian Blum,Andrea Roli,Michael Sampels
Hybrid Metaheuristics Book PDF

Author : Christian Blum,Andrea Roli,Michael Sampels
Publisher : Springer
Page : 290 pages
File Size : 46,9 Mb
Release : 2008-06-24
Category : Technology & Engineering
ISBN : 9783540782957

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Hybrid Metaheuristics by Christian Blum,Andrea Roli,Michael Sampels Pdf

Optimization problems are of great importance across a broad range of fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments. The authors involved in this book are among the top researchers in their domain.

Applying Particle Swarm Optimization

Burcu Adıgüzel Mercangöz
Applying Particle Swarm Optimization Book PDF

Author : Burcu Adıgüzel Mercangöz
Publisher : Springer Nature
Page : 355 pages
File Size : 44,5 Mb
Release : 2021-05-13
Category : Business & Economics
ISBN : 9783030702816

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Applying Particle Swarm Optimization by Burcu Adıgüzel Mercangöz Pdf

This book explains the theoretical structure of particle swarm optimization (PSO) and focuses on the application of PSO to portfolio optimization problems. The general goal of portfolio optimization is to find a solution that provides the highest expected return at each level of portfolio risk. According to H. Markowitz’s portfolio selection theory, as new assets are added to an investment portfolio, the total risk of the portfolio’s decreases depending on the correlations of asset returns, while the expected return on the portfolio represents the weighted average of the expected returns for each asset. The book explains PSO in detail and demonstrates how to implement Markowitz’s portfolio optimization approach using PSO. In addition, it expands on the Markowitz model and seeks to improve the solution-finding process with the aid of various algorithms. In short, the book provides researchers, teachers, engineers, managers and practitioners with many tools they need to apply the PSO technique to portfolio optimization.

Handbook of Metaheuristics

Michel Gendreau,Jean-Yves Potvin
Handbook of Metaheuristics Book PDF

Author : Michel Gendreau,Jean-Yves Potvin
Publisher : Springer
Page : 611 pages
File Size : 43,5 Mb
Release : 2018-09-20
Category : Business & Economics
ISBN : 9783319910864

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Handbook of Metaheuristics by Michel Gendreau,Jean-Yves Potvin Pdf

The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book’s chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.

Meta-Heuristics

Stefan Voß,Silvano Martello,Ibrahim H. Osman,Cathérine Roucairol
Meta Heuristics Book PDF

Author : Stefan Voß,Silvano Martello,Ibrahim H. Osman,Cathérine Roucairol
Publisher : Springer Science & Business Media
Page : 513 pages
File Size : 53,5 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9781461557753

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Meta-Heuristics by Stefan Voß,Silvano Martello,Ibrahim H. Osman,Cathérine Roucairol Pdf

Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.