Mathematical Modelling of Decision Problems

Mathematical Modelling of Decision Problems
Author: Nolberto Munier
Publisher: Springer Nature
Total Pages: 212
Release: 2021-10-19
Genre: Business & Economics
ISBN: 3030823474

This book is intended as a guide to and manual on modeling complex problems in Multi Criteria Decision Making (MCDM). It encourages practitioners to consider the practicalities of real-world scenarios when modeling, while at the same time providing tips and examples of how to incorporate these realities into the initial decision matrix. The goal is to help readers build a decision matrix that replicates reality as closely as possible. Once this matrix has been constructed, the Decision Maker (DM) can select from more than a hundred MCDM methods the one that best fits the requirements and conditions of the matrix. The book features cases taken from real-world scenarios, which deal with various fields, aspects, and characteristics, and are solved using the SIMUS (Sequential Interactive Modeling for Urban Systems) method. This book is a valuable tool for practitioners, researchers and students dealing with MCDM problems.

Mathematical Models for Decision Support

Mathematical Models for Decision Support
Author: Harvey J. Greenberg
Publisher: Springer Science & Business Media
Total Pages: 740
Release: 2012-12-06
Genre: Computers
ISBN: 3642835554

It is quite an onerous task to edit the proceedings of a two week long institute with learned contributors from many parts of the world. All the same, the editorial team has found the process of refereeing and reviewing the contributions worthwhile and completing the volume has proven to be a satisfying task. In setting up the institute we had considered models and methods taken from a number of different disciplines. As a result the whole institute - preparing for it, attending it and editing the proceedings - proved to be an intense learning experience for us. Here I speak on behalf of the committee and the editorial team. By the time the institute took place, the papers were delivered and the delegates exchanged their views, the structure of the topics covered and their relative positioning appeared in a different light. In editing the volume I felt compelled to introduce a new structure in grouping the papers. The contents of this volume are organised in eight main sections set out below: 1 . Abstracts. 2. Review Paper. 3. Models with Multiple Criteria and Single or Multiple Decision Makers. 4. Use of Optimisation Models as Decision Support Tools. 5. Role of Information Systems in Decision Making: Database and Model Management Issues. 6. Methods of Artificial Intelligence in Decision Making: Intelligent Knowledge Based Systems. 7. Representation of Uncertainty in Mathematical Models and Knowledge Based Systems. 8. Mathematical Basis for Constructing Models and Model Validation.

Mathematical Modeling and Computation of Real-Time Problems

Mathematical Modeling and Computation of Real-Time Problems
Author: Rakhee Kulshrestha
Publisher: CRC Press
Total Pages: 172
Release: 2021-01-04
Genre: Mathematics
ISBN: 1000288676

This book covers an interdisciplinary approach for understanding mathematical modeling by offering a collection of models, solved problems related to the models, the methodologies employed, and the results using projects and case studies with insight into the operation of substantial real-time systems. The book covers a broad scope in the areas of statistical science, probability, stochastic processes, fluid dynamics, supply chain, optimization, and applications. It discusses advanced topics and the latest research findings, uses an interdisciplinary approach for real-time systems, offers a platform for integrated research, and identifies the gaps in the field for further research. The book is for researchers, students, and teachers that share a goal of learning advanced topics and the latest research in mathematical modeling.

Modelling in Mathematical Programming

Modelling in Mathematical Programming
Author: José Manuel García Sánchez
Publisher: Springer
Total Pages: 284
Release: 2021-11-02
Genre: Business & Economics
ISBN: 9783030572525

This book provides basic tools for learning how to model in mathematical programming, from models without much complexity to complex system models. It presents a unique methodology for the building of an integral mathematical model, as well as new techniques that help build under own criteria. It allows readers to structure models from the elements and variables to the constraints, a basic modelling guide for any system with a new scheme of variables, a classification of constraints and also a set of rules to model specifications stated as logical propositions, helping to better understand models already existing in the literature. It also presents the modelling of all possible objectives that may arise in optimization problems regarding the variables values. The book is structured to guide the reader in an orderly manner, learning of the components that the methodology establishes in an optimization problem. The system includes the elements, which are all the actors that participate in the system, decision activities that occur in the system, calculations based on the decision activities, specifications such as regulations, impositions or actions of defined value and objective criterion, which guides the resolution of the system.

Mathematical Models for Decision Making with Multiple Perspectives

Mathematical Models for Decision Making with Multiple Perspectives
Author: Maria Isabel Gomes
Publisher: CRC Press
Total Pages: 301
Release: 2022-08-04
Genre: Mathematics
ISBN: 1000647579

This book brings together, in a single volume, the fields of multicriteria decision making and multiobjective optimization that are traditionally covered separately. Both fields have in common the presence of multiple perspectives of looking at and evaluating decisions to be taken but they differ in the number of available alternatives. Multicriteria approaches deal with decision processes where a finite number of alternatives have to be evaluated while, in multiobjective optimization, this number is infinite and the space of alternatives continuous. This book is written for students of applied mathematics, engineering, and economics and management, with no assumed previous knowledge on the subject, as well as for practitioners in industry looking for techniques to support decision making. The mathematical formalism is very low, so that all materials are accessible to most readers. Nonetheless, a rich bibliography allows interested readers to access more technical literature. The textbook is organized in eleven chapters, each corresponding to a class of about two hours. A comprehensive set of examples is presented, allowing for a didactic approach when presenting the methodologies. Each chapter ends with exercises that are designed to develop problem-solving skills and to promote concepts retention.

Mathematical Modeling

Mathematical Modeling
Author: Mark M. Meerschaert
Publisher: Elsevier
Total Pages: 360
Release: 2007-06-18
Genre: Mathematics
ISBN: 9780123708571

Mathematical Modeling, Third Edition is a general introduction to an increasingly crucial topic for today's mathematicians. Unlike textbooks focused on one kind of mathematical model, this book covers the broad spectrum of modeling problems, from optimization to dynamical systems to stochastic processes. Mathematical modeling is the link between mathematics and the rest of the world. Meerschaert shows how to refine a question, phrasing it in precise mathematical terms. Then he encourages students to reverse the process, translating the mathematical solution back into a comprehensible, useful answer to the original question. This textbook mirrors the process professionals must follow in solving complex problems. Each chapter in this book is followed by a set of challenging exercises. These exercises require significant effort on the part of the student, as well as a certain amount of creativity. Meerschaert did not invent the problems in this book--they are real problems, not designed to illustrate the use of any particular mathematical technique. Meerschaert's emphasis on principles and general techniques offers students the mathematical background they need to model problems in a wide range of disciplines. Increased support for instructors, including MATLAB material New sections on time series analysis and diffusion models Additional problems with international focus such as whale and dolphin populations, plus updated optimization problems

Methods of Mathematical Modelling and Computation for Complex Systems

Methods of Mathematical Modelling and Computation for Complex Systems
Author: Jagdev Singh
Publisher: Springer Nature
Total Pages: 433
Release: 2021-08-26
Genre: Technology & Engineering
ISBN: 3030771695

This book contains several contemporary topics in the areas of mathematical modelling and computation for complex systems. The readers find several new mathematical methods, mathematical models and computational techniques having significant relevance in studying various complex systems. The chapters aim to enrich the understanding of topics presented by carefully discussing the associated problems and issues, possible solutions and their applications or relevance in other scientific areas of study and research. The book is a valuable resource for graduate students, researchers and educators in understanding and studying various new aspects associated with complex systems. Key Feature • The chapters include theory and application in a mix and balanced way. • Readers find reasonable details of developments concerning a topic included in this book. • The text is emphasized to present in self-contained manner with inclusion of new research problems and questions.

Statistical Decision Problems

Statistical Decision Problems
Author: Michael Zabarankin
Publisher: Springer Science & Business Media
Total Pages: 254
Release: 2013-12-16
Genre: Business & Economics
ISBN: 1461484715

Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.

Decision Making Under Uncertainty

Decision Making Under Uncertainty
Author: Claude Greengard
Publisher: Springer Science & Business Media
Total Pages: 166
Release: 2012-12-06
Genre: Mathematics
ISBN: 146849256X

In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.