Optimalisering

"A wide-ranging intellectual history that reveals how important games have been to human progress, and what's at stake when we forget what games we're really playing. We play games to learn about the world, to understand our minds and the minds of others, and to make predictions about the future. Games are an essential aspect of humanity and a powerful tool for modeling reality. They're also a lot of fun. But games can be dangerous, especially when we mistake the model worlds of games for reality itself and let gamification co-opt human decision making. Playing with Reality explores the riveting history of games since the Enlightenment, weaving an unexpected path through military theory, political science, evolutionary biology, the development of computers and AI, cutting-edge neuroscience, and cognitive psychology. Neuroscientist and physicist Kelly Clancy shows how intertwined games have been with the arc of history. War games shaped the outcomes of real wars in nineteenth and twentieth century Europe. Game theory warped our understanding of human behavior and brought us to the brink of annihilation-yet still underlies basic assumptions in economics, politics, and technology design. We used games to teach computers how to learn for themselves, and now we are designing games that will determine the shape of society and future of democracy. In this revelatory new work, Clancy makes the bold argument that the human fascination with games is the key to understanding our nature and our actions"--

This book features chapters written by renowned scientists from various parts of the world, providing an up-to-date survey of submanifold theory, spanning diverse topics and applications. The book covers a wide range of topics such as Chen¿Ricci inequalities in differential geometry, optimal inequalities for Casorati curvatures in quaternion geometry, conformal ¿-Ricci¿Yamabe solitons, submersion on statistical metallic structure, solitons in f(R, T)-gravity, metric-affine geometry, generalized Wintgen inequalities, tangent bundles, and Lagrangian submanifolds. Moreover, the book showcases the latest findings on Pythagorean submanifolds and submanifolds of four-dimensional f-manifolds. The chapters in this book delve into numerous problems and conjectures on submanifolds, providing valuable insights for scientists, educators, and graduate students looking to stay updated with the latest developments in the field. With its comprehensive coverage and detailed explanations, this book is an essential resource for anyone interested in submanifold theory.

This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. In light of the big data revolution and the emergence of higher dimensional panel data sets, it provides new results to synthesize existing knowledge on the field. The first, theoretical part of the volume is providing the econometric foundations to deal with these new high-dimensional panel data sets. It not only synthesizes our current knowledge, but mostly, presents new research results. The second empirical part of the book provides insight into the most relevant applications in this area. These chapters are a mixture of surveys and new results, always focusing on the econometric problems and feasible solutions.This second extended and revised edition provides an update of all existent chapters to reflect on new developments in the area as well as several new chapters on topics such as machine learning, nonparametric models,networks, and multi-dimensional panels in health economics. The book serves as a standard reference work, a textbook for graduate students in economics, and a source of background material for professionals conducting empirical studies.

Statistical Analysis for Civil Engineers: Mathematical Theory and Applied Experiment Design is a well-researched and topically organized reference book that guides its readers, both in academia and industry, to recognize how to describe unpredictable events in a quantitative way and to learn how these events can be incorporated into practical engineering analysis that facilitates data-driven problem solving and optimization-based decision-making.Written by experts in the field with a proven track record as educators and practicing consultancy specialists, this book has been developed in such a manner that it advances understanding of the mathematical theory underlying analytical methodology gradually. It also supports practical application through relevant worked examples in a variety of civil engineering branches, notably structural, materials, transportation, and geotechnical engineering. Through all stages of data analysis, numerical modeling and simulation, and implementation, the volume emphasizes the need to change the current perception with respect to the use of modern statistical techniques in the scientific as well as practical spheres of civil engineering.

This book uses game theory to analyze the strategies developed in negotiation processes. Offering a detailed analysis of competition and cooperation, it explores various bargaining strategies that result from the application of Nash equilibrium and mixed strategies. Employing a blend of game theory and real-world examples, the authors describe typical negotiation scenarios and unveil the art of negotiation strategy ¿ dissecting both competitive and cooperative tactics.This comprehensive analysis explores the multifaceted dimensions of negotiation, highlighting not only formal aspects but also the economic, social, political, and human factors at play. The authors discuss the basic structures of cooperative and non-cooperative games and conduct a comprehensive analysis of the language games that take place in negotiations. They examine how negotiators belonging to different forms of life can trade with each other when their respective language games are different and prone tomisinterpretation. The book also probes arbitration and mediation as conflict-resolution tools within this intricate landscape. Designed for the curious minds seeking insight into negotiation strategies, as well as students and scholars of diverse fields, this book fosters an understanding of negotiation's labyrinthine pathways. "Dynamics of Rational Negotiation" unlocks the door to negotiation's complexities, inviting readers to unravel the layers of human interaction.

This book presents recent advances in the theory and application of the Best-Worst Method (BWM). It includes selected papers from the Second International Workshop on Best-Worst Method (BWM2021), held in Delft, The Netherlands from 10-11 June, 2021, and provides valuable insights on why and how to use BWM in a diverse range of applications including health, energy, supply chain management, and engineering. The book highlights the use of BWM in different settings including single decision-making vs group decision-making, and complete information vs incomplete and uncertain situations. The papers gathered here will benefit academics and practitioners who are involved in multi-criteria decision-making and decision analysis.

In this book, various chaos maps are embedded in eleven efficient and well-known metaheuristics and a significant improvement in the optimization results is achieved. The two basic steps of metaheuristic algorithms consist of exploration and exploitation. The imbalance between these stages causes serious problems for metaheuristic algorithms, which are immature convergence and stopping in local optima. Chaos maps with chaotic jumps can save algorithms from being trapped in local optima and lead to convergence toward global optima. Embedding these maps in the exploration phase, exploitation phase, or both simultaneously corresponds to three efficient and useful scenarios. By creating competition between different modes and increasing diversity in the search space and creating sudden jumps in the search phase, improvements are achieved for chaotic algorithms. Four Chaotic Algorithms, including Chaotic Cyclical Parthenogenesis Algorithm, Chaotic Water Evaporation Optimization, Chaotic Tug-of-War Optimization, and Chaotic Thermal Exchange Optimization are developed.

This book aims at introducing students into the modern analytical foundations to treat problems and situations in the Calculus of Variations solidly and rigorously. Since no background is taken for granted or assumed, as the textbook pretends to be self-contained, areas like basic Functional Analysis and Sobolev spaces are studied to the point that chapters devoted to these topics can be utilized by themselves as an introduction to these important parts of Analysis. The material in this regard has been selected to serve the needs of classical variational problems, leaving broader treatments for more advanced and specialized courses in those areas. It should not be forgotten that problems in the Calculus of Variations historically played a crucial role in pushing Functional Analysis as a discipline on its own right. The style is intentionally didactic. After a first general chapter to place optimization problems in infinite-dimensional spaces in perspective, the first part of the book focuses on the initial important concepts in Functional Analysis and introduces Sobolev spaces in dimension one as a preliminary, simpler case (much in the same way as in the successful book of H. Brezis). Once the analytical framework is covered, one-dimensional variational problems are examined in detail including numerous examples and exercises. The second part dwells, again as a first-round, on another important chapter of Functional Analysis that students should be exposed to, and that eventually will find some applications in subsequent chapters. The first chapter of this part examines continuous operators and the important principles associated with mappings between functional spaces; and another one focuses on compact operators and their fundamental and remarkable properties for Analysis. Finally, the third part advances to multi-dimensional Sobolev spaces and the corresponding problems in the Calculus of Variations. In this setting, problems become much more involved and, for this same reason, much more interesting and appealing. In particular, the final chapter dives into a number of advanced topics, some of which reflect a personal taste. Other possibilities stressing other kinds of problems are possible. In summary, the text pretends to help students with their first exposure to the modern calculus of variations and the analytical foundation associated with it. In particular, it covers an extended introduction to basic functional analysis and to Sobolev spaces. The tone of the text and the set of proposed exercises will facilitate progressive understanding until the need for further challenges beyond the topics addressed here will push students to more advanced horizons.

Commissioned by the Society for Modeling and Simulation International (SCS), this needed, useful new ¿Body of Knowledge¿ (BoK) collects and organizes the common understanding of a wide collection of professionals and professional associations.Modeling and simulation (M&S) is a ubiquitous discipline that lays the computational foundation for real and virtual experimentation, clearly stating boundaries¿and interactions¿of systems, data, and representations. The field is well known, too, for its training support via simulations and simulators. Indeed, with computers increasingly influencing the activities of today¿s world, M&S is the third pillar of scientific understanding, taking its place along with theory building and empirical observation.This valuable new handbook provides intellectual support for all disciplines in analysis, design and optimization. It contributes increasingly to the growing number of computational disciplines, addressing the broad variety of contributing as well as supported disciplines and application domains. Further, each of its sections provide numerous references for further information. Highly comprehensive, the BoK represents many viewpoints and facets, captured under such topics as:Mathematical and Systems Theory FoundationsSimulation Formalisms and ParadigmsSynergies with Systems Engineering and Artificial IntelligenceMultidisciplinary ChallengesEthics and PhilosophyHistorical PerspectivesExamining theoretical as well as practical challenges, this unique volume addresses the many facets of M&S for scholars, students, and practitioners. As such, it affords readers from all science, engineering, and arts disciplines a comprehensive and concise representation of concepts, terms, and activities needed to explain the M&S discipline.Tuncer Ören is Professor Emeritus at the University of Ottawa. Bernard Zeigler is Professor Emeritus at the University of Arizona. Andreas Tolk is Chief Scientist at The MITRE Corporation. All three editors are long-time members and Fellows of the Society for Modeling and Simulation International. Under the leadership of three SCS Fellows, Dr. Ören, University of Ottawa, Dr. Zeigler, The University of Arizona, and Dr. Tolk, The MITRE Corporation, more than 50 international scholars from 15 countries provided insights and experience to compile this initial M&S Body of Knowledge.

This thesis deals with storage systems that are organized in last-in-first-out stacks. This approach for storing items is common, for example, in container terminals, and is therefore of great practical interest as well as high relevance in the literature. Furthermore, optimization problems that may arise in this context are presented and addressed by developing novel mathematical model formulations and customized solution methods.

Optimization should be the science of making the best possible decisions. Making decisions is a virtually universal human activity encountered by professionals (in any field) or people in their everyday lives. You would think, then, that the study of making good decisions is a subject that should be taught broadly to students throughout engineering, the physical and social sciences, business, and policy. Yet today, "optimization" is widely taught as a mathematically sophisticated subject, often limited to graduate students in specialized fields.In operations research (or industrial engineering), "optimization" is equivalent to deterministic math programming, starting with linear programs (and the simplex algorithm), and then transitioning through integer linear programs and nonlinear programs. If you are in departments like electrical or mechanical engineering, optimization means teaching optimal control. And if you are in computer science, optimization today could be interpreted in the context of machine learning (such as fitting models to data) or as reinforcement learning.This book claims that the traditional style of teaching optimization is misguided and out of date. First, while the simplex algorithm is a powerful strategy for solving linear programs, the details of the simplex algorithm are completely inappropriate in an introductory course in optimization. Second, while linear programs are appropriate for solving many problems, they are only applicable to a tiny fraction of all decisions. Third, linear programs (along with integer and nonlinear programs) are static models for problems with (typically) vector-valued decisions. By contrast, most decisions are sequential since they are made periodically over time as new information is arriving. In addition, the vast majority of these decisions are scalar (possibly continuous or discrete).This book is designed for instructors (or potential instructors) looking to introduce the science of making good decisions to the broadest possible audience. It should also be of interest to anyone who has already had a traditional course in optimization of any type. The presentation is organized around a series of topics that suggest a fundamentally different approach to teaching "optimization" spanning both sequential decision problems (which offer the simplest problem settings) before transitioning to more complex vector-valued decisions. It also makes the case that most problems which are modeled as linear (or integer, or nonlinear programs) are actually methods for making decisions in a sequential setting. For this reason, these topics are introduced with much less emphasis on algorithms than is traditionally used, both in static and sequential settings.

This book presents a comprehensive framework for developing Industry 4.0 and 5.0 solutions through the use of ontology modeling and graph-based optimization techniques. With effective information management being critical to successful manufacturing processes, this book emphasizes the importance of adequate modeling and systematic analysis of interacting elements in the era of smart manufacturing.The book provides an extensive overview of semantic technologies and their potential to integrate with existing industrial standards, planning, and execution systems to provide efficient data processing and analysis. It also investigates the design of Industry 5.0 solutions and the need for problem-specific descriptions of production processes, operator skills and states, and sensor monitoring in intelligent spaces.The book proposes that ontology-based data can efficiently represent enterprise and manufacturing datasets.The book is divided into two parts: modelingand optimization. The semantic modeling part provides an overview of ontologies and knowledge graphs that can be used to create Industry 4.0 and 5.0 applications, with two detailed applications presented on a reproducible industrial case study. The optimization part of the book focuses on network science-based process optimization and presents various detailed applications, such as graph-based analytics, assembly line balancing, and community detection.The book is based on six key points: the need for horizontal and vertical integration in modern industry; the potential benefits of integrating semantic technologies into ERP and MES systems; the importance of optimization methods in Industry 4.0 and 5.0 concepts; the need to process large amounts of data while ensuring interoperability and re-usability factors; the potential for digital twin models to model smart factories, including big data access; and the need to integrate human factors in CPSs and provide adequate methods tofacilitate collaboration and support shop floor workers.

This monograph presents the most recent developments in the study of Hamilton-Jacobi Equations and control problems with discontinuities, mainly from the viewpoint of partial differential equations. Two main cases are investigated in detail: the case of codimension 1 discontinuities and the stratified case in which the discontinuities can be of any codimensions. In both, connections with deterministic control problems are carefully studied, and numerous examples and applications are illustrated throughout the text.After an initial section that provides a ¿toolbox¿ containing key results which will be used throughout the text, Parts II and III completely describe several recently introduced approaches to treat problems involving either codimension 1 discontinuities or networks. The remaining sections are concerned with stratified problems either in the whole space R^N or in bounded or unbounded domains with state-constraints. In particular, the use of stratified solutions to treat problems with boundary conditions, where both the boundary may be non-smooth and the data may present discontinuities, is developed. Many applications to concrete problems are explored throughout the text ¿ such as Kolmogorov-Petrovsky-Piskunov (KPP) type problems, large deviations, level-sets approach, large time behavior, and homogenization ¿ and several key open problems are presented.This monograph will be of interest to graduate students and researchers working in deterministic control problems and Hamilton-Jacobi Equations, network problems, or scalar conservation laws.

Each of the "Keys to the Kingdom" Advanced Training Course Manuals will further a Seekers reach on the Pathway leading out of this Universe.

Each of the "Keys to the Kingdom" Advanced Training Course Manuals will further a Seekers reach on the Pathway leading out of this Universe.

"Get up-to-speed with the fundamentals of how electricity markets are structured and operated with this comprehensive textbook, requiring no prior experience in power systems or energy economics. An ideal introduction for senior undergraduate and graduate students in electrical engineering, economics, and operations research"--