Optimalisering

Akademische Arbeit aus dem Jahr 2021 im Fachbereich Medien / Kommunikation - Medienökonomie, -management, Note: 1,7, Hochschule Fresenius; Hamburg, Sprache: Deutsch, Abstract: Das Ziel dieser Arbeit ist es, die Grundzüge der Spieltheorie zu erläutern und spieltheoretische Mechanismen anhand von realen Praxisbeispielen in der digitalen Ökonomie zu analysieren. Da die Spieltheorie ein spezieller Teil der Entscheidungstheorie ist, wird im ersten Kapitel des Hauptteils zuerst die Entscheidungstheorie grundlegend erklärt, bevor die Grundzüge der Spieltheorie beschrieben werden. Anschließend wird die historische Entwicklung der Spieltheorie erläutert, ehe simultane und sequentielle sowie Spiele mit perfekter und imperfekter Information betrachtet werden. Danach wird auf die beiden verschiedenen spieltheoretischen Darstellungsformen eingegangen. Zum Abschluss des theoretischen Teils wird die Spieltheorie in den Kontext des digitalen Managements eingeordnet. Im dritten Kapitel werden schließlich die digitalen Geschäftsmodelle von Booking.com, Google Ads und eBay auf spieltheoretische Mechanismen untersucht und somit die Nutzung der Spieltheorie in der digitalen Wirtschaft überprüft. Zuletzt wird im Fazit die Untersuchung zusammengefasst und eine Einschätzung zur Nutzung der Spieltheorie in der digitalen Ökonomie gegeben.

Studienarbeit aus dem Jahr 2017 im Fachbereich Ingenieurwissenschaften - Wirtschaftsingenieurwesen, Note: 1,7, Duale Hochschule Baden-Württemberg, Stuttgart, früher: Berufsakademie Stuttgart, Sprache: Deutsch, Abstract: Die vorliegende Arbeit erläutert das Modell der Spieltheorie und stellt verschiedene Ausprägungen von Spielen dar. Anhand einfacher Beispiele sollen Parallelen zu internationalen oder medial präsenten Konflikten aufgezeigt werden. Eine praktische Anwendung der Methoden wird bei Fallbeispielen aus Politik und Wirtschaft vollzogen. Es sollen anhand spieltheoretischer Ansätze die Handlungsalternativen der beteiligten Spieler aufgezeigt und Strategien definiert werden.Bei der Anbahnung eines Konflikts oder einer anstehenden Entscheidung betrachtet man oftmals nur die eigene Situation. Die klassische Entscheidungstheorie dient hierbei als Hilfsmittel und versucht, aus mehreren Alternativen die für den Entscheider optimale zu finden. Hierfür gibt sie Hilfestellungen, wie Menschen rationale Entscheidungen treffen können und will erklären, wie reale Entscheidungen zustande kommen. Für die Ordnung der Entscheidungsergebnisse müssen diese nicht nur bekannt sein, sondern auch bewertet werden können. Betrachtet werden dabei Individuen, Gruppen und Organisationen. Da die Wahl einer Alternative nicht durch das Handeln anderer Akteure beeinflusst wird, bestehen keine Interdependenzen. In der Realität sind aber oftmals genau solche Abhängigkeiten zu anderen Entscheidungsträgern vorhanden, welche das eigene Handeln elementar beeinflussen können. Die Interaktionen anderer beteiligter Parteien dürfen daher bei Entscheidungen nicht außer Acht gelassen werden. Da die klassische Entscheidungstheorie bei solchen Fällen kein Ergebnis liefern kann, möchte die Spieltheorie erweiterte Lösungsansätze bereitstellen. Sie wird ebenfalls zu den Entscheidungstheorien gezählt und befasst sich mit der Frage, wie ein Individuum oder eine Gruppe entscheidet, wenn sowohl das eigene Handeln als auch die Aktionen interdependenter Akteure Einfluss auf das Ergebnis der Entscheidung besitzen.

This text is an introduction to Operations Management. Three themes are woven throughout the book: optimization or trying to do the best we can, managing tradeoffs between conflicting objectives, and dealing with uncertainty. After a brief introduction, the text reviews the fundamentals of probability including commonly used discrete and continuous distributions and functions of a random variable. The next major section, beginning in Chapter 7, examines optimization. The key fundamentals of optimization-inputs, decision variables, objective(s), and constraints-are introduced. Optimization is applied to linear regression, basic inventory modeling, and the newsvendor problem, which incorporates uncertain demand. Linear programming is then introduced. We show that the newsvendor problem can be cast as a network flow linear programming problem. Linear programming is then applied to the problem of redistributing empty rental vehicles (e.g., bicycles) at the end of a day and the problem of assigning students to seminars. Several chapters deal with location models as examples of both simple optimization problems and integer programming problems. The next major section focuses on queueing theory including single-and multi-server queues. This section also introduces a numerical method for solving for key performance metrics for a common class of queueing problems as well as simulation modeling. Finally, the text ends with a discussion of decision theory that again integrates notions of optimization, tradeoffs, and uncertainty analysis. The text is designed for anyone with a modest mathematical background. As such, it should be readily accessible to engineering students, economics, statistics, and mathematics majors, as well as many business students.

Recent data shows that 87% of Artificial Intelligence/Big Data projects don't make it into production (VB Staff, 2019), meaning that most projects are never deployed. This book addresses five common pitfalls that prevent projects from reaching deployment and provides tools and methods to avoid those pitfalls. Along the way, stories from actual experience in building and deploying data science projects are shared to illustrate the methods and tools. While the book is primarily for data science practitioners, information for managers of data science practitioners is included in the Tips for Managers sections.

This book constitutes the refereed proceedings of the 22nd International Conference on Group Decision and Negotiation, GDN 2022, which was held virtually during June 12-16, 2022. The field of Group Decision and Negotiation focuses on decision processes with at least two participants and a common goal but conflicting individual goals. Research areas of Group Decision and Negotiation include electronic negotiations, experiments, the role of emotions in group decision and negotiations, preference elicitation and decision support for group decisions and negotiations, and conflict resolution principles. This year's conference focusses on methodological and practical issues.The 9 full papers presented in this volume were carefully reviewed and selected from 68 submissions. They were organized in the following topical sections: Preference modeling for group decision and negotiation; conflict resolution; collaborative decision making processes.  

“Exactly the message we need to counter the mythology of the ‘rugged individual’” (Bill Moyers, Progressive Reader).Martin Nowak, one of the world’s experts on evolution and game theory, working here with bestselling science writer Roger Highfield, turns an important aspect of evolutionary theory on its head to explain why cooperation, not competition, has always been the key to the evolution of complexity. In his first book written for a wide audience, this hugely influential scientist explains his cutting-edge research into the mysteries of cooperation, from the rise of multicellular life to Good Samaritans, and from cancer treatment to the success of large companies. With wit and clarity, and an eye to its huge implications, Nowak and Highfield make the case that cooperation, not competition, is the defining human trait. SuperCooperators will expand our understanding of evolution and provoke debate for years to come.

This book presents a survey of the aspects of economic complexity, with a focus on foundational, interdisciplinary ideas. The long-awaited follow up to his 2011 volume Complex Evolutionary Dynamics in Urban-Regional and Ecologic-Economic Systems: From Catastrophe to Chaos and Beyond, this volume draws together the threads of Rosser¿s earlier work on complexity theory and its wide applications in economics and an expanded list of related disciplines. The book begins with a full account of the broader categories of complexity in economics--dynamic, computational, hierarchical, and structural--before shifting to more detailed analysis. The next two chapters address problems associated with computational complexity, especially those of computability, and discuss the Godel Incompleteness Theorem with a focus on reflexivity. The middle chapters discuss the relationship between entropy, econophysics, evolution, and economic complexity, respectively, with applications in urban and regional dynamics, ecological economics, general equilibrium theory, as well as financial market dynamics. The final chapter works to bring together these themes into a broader framework and expose some of the limits concerning analysis of deeper foundational issues.With applications in all disciplines characterized by interconnected nonlinear adaptive systems, this book is appropriate for graduate students, professors and practitioners in economics and related disciplines such as regional science, mathematics, physics, biology, environmental sciences, philosophy, and psychology.

A Course in Topological Combinatorics is the first undergraduate textbook on the field of topological combinatorics, a subject that has become an active and innovative research area in mathematics over the last thirty years with growing applications in math, computer science, and other applied areas. Topological combinatorics is concerned with solutions to combinatorial problems by applying topological tools. In most cases these solutions are very elegant and the connection between combinatorics and topology often arises as an unexpected surprise.The textbook covers topics such as fair division, graph coloring problems, evasiveness of graph properties, and embedding problems from discrete geometry. The text contains a large number of figures that support the understanding of concepts and proofs. In many cases several alternative proofs for the same result are given, and each chapter ends with a series of exercises. The extensive appendix makes the book completely self-contained.The textbook is well suited for advanced undergraduate or beginning graduate mathematics students. Previous knowledge in topology or graph theory is helpful but not necessary. The text may be used as a basis for a one- or two-semester course as well as a supplementary text for a topology or combinatorics class.

In the spectrum of mathematics, graph theory which studies a mathe- matical structure on a set of elements with a binary relation, as a recognized discipline, is a relative newcomer. In recent three decades the exciting and rapidly growing area of the subject abounds with new mathematical devel- opments and significant applications to real-world problems. More and more colleges and universities have made it a required course for the senior or the beginning postgraduate students who are majoring in mathematics, computer science, electronics, scientific management and others. This book provides an introduction to graph theory for these students. The richness of theory and the wideness of applications make it impossi- ble to include all topics in graph theory in a textbook for one semester. All materials presented in this book, however, I believe, are the most classical, fundamental, interesting and important. The method we deal with the mate- rials is to particularly lay stress on digraphs, regarding undirected graphs as their special cases. My own experience from teaching out of the subject more than ten years at University of Science and Technology of China (USTC) shows that this treatment makes hardly the course di:fficult, but much more accords with the essence and the development trend of the subject.

Primary Audience for the Book * Specialists in numerical computations who are interested in algorithms with automatic result verification. * Engineers, scientists, and practitioners who desire results with automatic verification and who would therefore benefit from the experience of suc- cessful applications. * Students in applied mathematics and computer science who want to learn these methods. Goal Of the Book This book contains surveys of applications of interval computations, i. e. , appli- cations of numerical methods with automatic result verification, that were pre- sented at an international workshop on the subject in EI Paso, Texas, February 23-25, 1995. The purpose of this book is to disseminate detailed and surveyed information about existing and potential applications of this new growing field. Brief Description of the Papers At the most fundamental level, interval arithmetic operations work with sets: The result of a single arithmetic operation is the set of all possible results as the operands range over the domain. For example, [0. 9,1. 1] + [2. 9,3. 1] = [3. 8,4. 2], where [3. 8,4. 2] = {x + ylx E [0. 9,1. 1] and y E [3. 8,4. 2]}. The power of interval arithmetic comes from the fact that (i) the elementary operations and standard functions can be computed for intervals with formulas and subroutines; and (ii) directed roundings can be used, so that the images of these operations (e. g.