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Nonlinear Multiobjective Optimization
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ISBN: 0792382781 1461375444 1461555639 9780792382782 Year: 1998 Publisher: New York, NY : Springer US : Imprint: Springer,

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Problems with multiple objectives and criteria are generally known as multiple criteria optimization or multiple criteria decision-making (MCDM) problems. So far, these types of problems have typically been modelled and solved by means of linear programming. However, many real-life phenomena are of a nonlinear nature, which is why we need tools for nonlinear programming capable of handling several conflicting or incommensurable objectives. In this case, methods of traditional single objective optimization and linear programming are not enough; we need new ways of thinking, new concepts, and new methods - nonlinear multiobjective optimization. Nonlinear Multiobjective Optimization provides an extensive, up-to-date, self-contained and consistent survey, review of the literature and of the state of the art on nonlinear (deterministic) multiobjective optimization, its methods, its theory and its background. The amount of literature on multiobjective optimization is immense. The treatment in this book is based on approximately 1500 publications in English printed mainly after the year 1980. Problems related to real-life applications often contain irregularities and nonsmoothnesses. The treatment of nondifferentiable multiobjective optimization in the literature is rather rare. For this reason, this book contains material about the possibilities, background, theory and methods of nondifferentiable multiobjective optimization as well. This book is intended for both researchers and students in the areas of (applied) mathematics, engineering, economics, operations research and management science; it is meant for both professionals and practitioners in many different fields of application. The intention has been to provide a consistent summary that may help in selecting an appropriate method for the problem to be solved. It is hoped the extensive bibliography will be of value to researchers.


Book
Evolutionary Multi-objective Optimization : An Honorary Issue Dedicated to Professor Kalyanmoy Deb
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ISBN: 3036569812 3036569804 Year: 2023 Publisher: Basel : MDPI - Multidisciplinary Digital Publishing Institute,

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This volume is a reprint of the Honorary Special Issue dedicated to the 60th birthday of Professor Dr. Kalyanmoy Deb, published in the journal Mathematical and Computational Applications (MCA). Kalyanmoy Deb has been a pioneer and highly impactful and influential proponent of Evolutionary Multi-objective Optimization (EMO) since 1994. He is currently a Koenig Endowed Chair Professor and University Distinguished Professor in the Department of Electrical and Computer Engineering at Michigan State University, USA, and holds additional appointments in Mechanical Engineering and in Computer Science and Engineering. Professor Deb's research interests are in evolutionary optimization and its application in multi-objective optimization, modeling, machine learning, and in multi-objective decision making. He has been a visiting professor at various universities across the world, including IITs in India, Aalto University in Finland, the University of Skovde in Sweden, and Nanyang Technological University in Singapore. He was awarded the IEEE Evolutionary Computation Pioneer Award, the Infosys Prize, the TWAS Prize in Engineering Sciences, the CajAstur Mamdani Prize, the Distinguished Alumni Award from IIT Kharagpur, the Edgeworth Pareto Award, the Bhatnagar Prize in Engineering Sciences, and the Bessel Research Award from Germany. He is a fellow of IEEE, ASME, and three Indian science and engineering academies.


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Evolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings
Authors: --- --- --- --- --- et al.
ISBN: 303012598X 3030125971 Year: 2019 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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This book constitutes the refereed proceedings of the 10th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2019 held in East Lansing, MI, USA, in March 2019. The 59 revised full papers were carefully reviewed and selected from 76 submissions. The papers are divided into 8 categories, each representing a key area of current interest in the EMO field today. They include theoretical developments, algorithmic developments, issues in many-objective optimization, performance metrics, knowledge extraction and surrogate-based EMO, multi-objective combinatorial problem solving, MCDM and interactive EMO methods, and applications.

Keywords

Computer software. --- Artificial intelligence. --- Computer science. --- Computer Communication Networks. --- Data structures (Computer scienc. --- Algorithm Analysis and Problem Complexity. --- Artificial Intelligence. --- Models and Principles. --- Mathematics of Computing. --- Data Structures. --- Data structures (Computer science) --- Informatics --- Science --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Software, Computer --- Computer systems --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Mathematical optimization --- Algorithms. --- Computers. --- Computer science—Mathematics. --- Computer communication systems. --- Data structures (Computer science). --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Cybernetics --- Calculators --- Cyberspace --- Algorism --- Algebra --- Arithmetic --- Distributed processing --- Foundations --- Computer networks. --- Artificial intelligence—Data processing. --- Models of Computation. --- Data Science.


Book
Multiobjective Optimization : Interactive and Evolutionary Approaches
Authors: --- --- --- ---
ISBN: 9783540889083 Year: 2008 Publisher: Berlin Heidelberg Springer Berlin Heidelberg

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Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.


Book
Evolutionary Multi-Criterion Optimization
Authors: --- --- --- --- --- et al.
ISBN: 9783030125981 Year: 2019 Publisher: Cham Springer International Publishing :Imprint: Springer

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Evolutionary Multi-Criterion Optimization
Authors: --- --- --- --- --- et al.
ISBN: 9783031272509 Year: 2023 Publisher: Cham Springer Nature Switzerland :Imprint: Springer

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Multiobjective optimization : interactive and evolutionary approaches

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