Mathematical Modelling of Decision Problems
Mathematical Modelling of Decision Problems

Author: Nolberto Munier

Publisher: Springer Nature

Published: 2021-10-19

Total Pages: 212

ISBN-13: 3030823474

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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

Published: 2012-12-06

Total Pages: 740

ISBN-13: 3642835554

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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.

Modelling in Mathematical Programming
Modelling in Mathematical Programming

Author: José Manuel García Sánchez

Publisher: Springer

Published: 2021-11-02

Total Pages: 284

ISBN-13: 9783030572525

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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 Modeling
Mathematical Modeling

Author: Mark M. Meerschaert

Publisher: Elsevier

Published: 2007-06-18

Total Pages: 360

ISBN-13: 9780123708571

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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

Mathematical Modeling and Computation of Real-Time Problems
Mathematical Modeling and Computation of Real-Time Problems

Author: Rakhee Kulshrestha

Publisher: CRC Press

Published: 2021-01-04

Total Pages: 172

ISBN-13: 1000288676

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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.

Foundations of Mathematical Modelling for Engineering Problem Solving
Foundations of Mathematical Modelling for Engineering Problem Solving

Author: Parikshit Narendra Mahalle

Publisher: Springer Nature

Published: 2023-01-10

Total Pages: 177

ISBN-13: 9811988285

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This book aims at improving the mathematical modelling skills of users by enhancing the ability to understand, connect, apply and use the mathematical concepts to the problem at hand. This book provides the readers with an in-depth knowledge of the various categories/classes of research problems that professionals, researchers and students might encounter following which the applications of appropriate mathematical models is explained with the help of case studies. The book is targeted at academicians, researchers, students and professionals who belong to all engineering disciplines.

Statistical Decision Problems
Statistical Decision Problems

Author: Michael Zabarankin

Publisher: Springer Science & Business Media

Published: 2013-12-16

Total Pages: 254

ISBN-13: 1461484715

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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.

Mathematical Modelling in Engineering & Human Behaviour 2018
Mathematical Modelling in Engineering & Human Behaviour 2018

Author: Lucas Jódar

Publisher: MDPI

Published: 2019-04-15

Total Pages: 196

ISBN-13: 3038978043

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This book includes papers in cross-disciplinary applications of mathematical modelling: from medicine to linguistics, social problems, and more. Based on cutting-edge research, each chapter is focused on a different problem of modelling human behaviour or engineering problems at different levels. The reader would find this book to be a useful reference in identifying problems of interest in social, medicine and engineering sciences, and in developing mathematical models that could be used to successfully predict behaviours and obtain practical information for specialised practitioners. This book is a must-read for anyone interested in the new developments of applied mathematics in connection with epidemics, medical modelling, social issues, random differential equations and numerical methods.

Decision Making Under Uncertainty
Decision Making Under Uncertainty

Author: Claude Greengard

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 166

ISBN-13: 146849256X

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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.

Advanced Mathematical Modeling with Technology
Advanced Mathematical Modeling with Technology

Author: William P. Fox

Publisher: CRC Press

Published: 2021-05-19

Total Pages: 573

ISBN-13: 1000388867

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Mathematical modeling is both a skill and an art and must be practiced in order to maintain and enhance the ability to use those skills. Though the topics covered in this book are the typical topics of most mathematical modeling courses, this book is best used for individuals or groups who have already taken an introductory mathematical modeling course. This book will be of interest to instructors and students offering courses focused on discrete modeling or modeling for decision making.