Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Apart from Chapter 1, which reviews classical training methods, the chapters are divided into three main categories. The first one is devoted to local search based methods, including Simulated Annealing, Tabu Search, and Variable Neighborhood Search. The second part of the book presents population based methods, such as Estimation Distribution algorithms, Scatter Search, and Genetic Algorithms. The third part covers other advanced techniques, such as Ant Colony Optimization, Co-evolutionary methods, GRASP, and Memetic algorithms. Overall, the book's objective is engineered to provide a broad coverage of the concepts, methods, and tools of this important area of ANNs within the realm of continuous optimization.

This book is a compilation of a selected subset of research articles presented at the Eighth INFORMS Computing Society Conference, held in Chandler, Arizona, from January 8 to 10, 2003. The articles in this book represent the diversity and depth of the interface between ORiMS (operations research and the management sciences) and CS/AI (computer science and artificial intelligence ). This volume starts with two papers that represent the reflective and integrative thinking that is critical to any scientific discipline.

This book is intended to provide an introductory text of Nonlinear and Dynamic Programming for students of managerial economics and operations research. The author also hopes that engineers, business executives, managers, and others responsible for planning of industrial operations may find it useful as a guide to the problems and methods treated, with a view to practical applications. The book may be considered as a sequel to the author's Linear Programming in Industry (1960, 4th revised and enlarged edition 1974), but it can be used independently by readers familiar with the elements of linear programming models and techniques. The two volumes con­ stitute an introduction to the methods of mathematical programming and their application to industrial optimization problems. The author feels that the vast and ever-increasing literature on mathematical programming has not rendered an introductory exposition super­ fluous. The general student often tends to feel somewhat lost if he goes straight to the special literature; he will be better equipped for tackling real problems and using computer systems if he has acquired some previous training in constructing small-scale programming models and applying standard algorithms for solving them by hand. The book is intended to provide this kind of training, keeping the mathematics at the necessary minimum. The text contains numerous exercises. The reader should work out these problems for himself and check with the answers given at the end of the book. The text is based on lectures given at the University of Copenhagen.

Written by a leading researcher this book presents an introduction to Stochastic Petri Nets covering the modeling power of the proposed SPN model, the stability conditions and the simulation methods. Its unique and well-written approach provides a timely and important addition to the literature. Appeals to a wide range of researchers in engineering, computer science, mathematics and OR.

This book (proceedings of ISMS 2022) is intended to be used as a reference by students and researchers who collect scientific and technical contributions with respect to models, tools, technologies and applications in the field of information systems and management science. This textbook shows how to exploit information systems in a technology-rich management field. The book introduces concepts, principles, methods, and procedures that will be valuable to students and scholars in thinking about existing organization systems, proposing new systems, and working with management professionals in implementing new information systems.

The papers published in this volume focus on some of the most recent devel- ments in complementarity theory, variational principles, stability theory of fu- tional equations, nonsmooth optimization, and various other important topics of nonlinear analysis and optimization. This volume was initially planned to celebrate Professor George Isac’s 70th birthday by bringing together research scientists from mathematical domains which have long bene ted from Isac’s active research passion. Unfortunately, George Isac passed away in February 2009 at the age of 69. George Isac received his Ph. D. in 1973 from the Institute of Mathematics of the Romanian Academy of Sciences. He made outstanding contributions in s- eral branches of pure and applied mathematics, including complementarity theory, variational inequalities, xed point theory, scalar and vector optimization, theory of cones, eigenvalue problems, convex analysis, variational principles and regulari- tion methods, as well as a number of other topics. In his long and outstanding career, he wrote more than 200 papers and 13 books. Professor Isac was an avid traveler who visited more than 70 universities around the globe and delivered approximately 180 research presentations. He also authored seven books on poetry. During his s- enti c career he collaborated with numerous mathematicians. His research papers contain very deep, original and beautiful results. Through his signi cant contri- tions, he earned a distinguished position and became an internationally renowned leading scholar in his research elds.

The main theorem of Linear Programming Duality, relating a "pri­ mal" Linear Programming problem to its "dual" and vice versa, can be seen as a statement about sign patterns of vectors in complemen­ tary subspaces of Rn. This observation, first made by R.T. Rockafellar in the late six­ ties, led to the introduction of certain systems of sign vectors, called "oriented matroids". Indeed, when oriented matroids came into being in the early seventies, one of the main issues was to study the fun­ damental principles underlying Linear Progra.mrning Duality in this abstract setting.

This book presents important insights into Social Innovation and Reverse Innovation. It introduces a unique perspective by merging Social Innovation with the emerging concept of Reverse Innovation. Addressing the scarcity of Reverse Innovation knowledge, the book starts with a comprehensive literature review, establishing a solid theoretical framework.

In mathematical modeling of processes occurring in logistics, management science, operations research, networks, mathematical finance, medicine, and control theory, one often encounters optimization problems involving more than one objective function so that Multiobjective Optimization (or Vector Optimization, initiated by W. Pareto) has received new impetus. The growing interest in vector optimization problems, both from the theoretical point of view and as it concerns applications to real world optimization problems, asks for a general scheme which embraces several existing developments and stimulates new ones.

Production planning problems containing special characteristics from process industries are addressed in this book. The main subject is the development of mathematical programming models that allow to model production plans which are not disrupted by discretization of time. However, discrete time models are used as a basis and are subsequently enhanced to include aspects of time continuity. Their integration is achieved by different building blocks which may be combined freely according to the specific planning situation at hand. The primary area of application of these kinds of models are process industries.

After developing fuzzy set theory, many contributors focused their research on the extension of fuzzy sets and their computational methodologies, strengthening modern science and technology. In some real-life phenomena, the conventional methods and traditional fuzzy sets cannot be explained, whereas the extension of fuzzy sets and effective new computing methods can explain it adequately.

Swarm intelligence is a modern arti?cial intelligence discipline that is c- cerned with the design of multiagent systems with applications, e.g., in - timization and in robotics. The design paradigm for these systems is fun- mentally di?erent from more traditional approaches. Instead of a sophisticated controller that governs the global behavior of the system, the swarm intelligence principle is based on many unsophisticated entities that cooperate in order to exhibit a desired behavior. Inspiration for the design of these systems is taken from the collective behavior of social insects such as ants, termites, bees, and wasps, as well as from the behavior of other animalsocietiessuchas?ocksofbirdsorschoolsof?

This book gathers selected high-quality papers presented at the 31st European Conference on Operational Research, which was held in Athens, Greece on June 11-14, 2021. It highlights the latest advances in the application of operations research (OR) to technology-driven areas in business, finance, and economics, covering both theoretical and methodological developments, as well as real-world case studies. It also explores the connections between OR and other analytical disciplines, such as soft computing and computer science, which can promote the development of new decision support technologies.