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Quantitative Finance: A Simulation-Based Introduction Using Excel
by Matt DavisonTeach Your Students How to Become Successful Working QuantsQuantitative Finance: A Simulation-Based Introduction Using Excel provides an introduction to financial mathematics for students in applied mathematics, financial engineering, actuarial science, and business administration. The text not only enables students to practice with the basic techn
Quantitative Finance: An Object-Oriented Approach in C++ (Chapman and Hall/CRC Financial Mathematics Series)
by Erik SchloglQuantitative Finance: An Object-Oriented Approach in C++ provides readers with a foundation in the key methods and models of quantitative finance. Keeping the material as self-contained as possible, the author introduces computational finance with a focus on practical implementation in C++. Through an approach based on C++ classes and templates, the text highlights the basic principles common to various methods and models while the algorithmic implementation guides readers to a more thorough, hands-on understanding. By moving beyond a purely theoretical treatment to the actual implementation of the models using C++, readers greatly enhance their career opportunities in the field. The book also helps readers implement models in a trading or research environment. It presents recipes and extensible code building blocks for some of the most widespread methods in risk management and option pricing. Web ResourceThe author’s website provides fully functional C++ code, including additional C++ source files and examples. Although the code is used to illustrate concepts (not as a finished software product), it nevertheless compiles, runs, and deals with full, rather than toy, problems. The website also includes a suite of practical exercises for each chapter covering a range of difficulty levels and problem complexity.
Quantitative Finance with Python: A Practical Guide to Investment Management, Trading, and Financial Engineering (Chapman and Hall/CRC Financial Mathematics Series)
by Chris KelliherQuantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. Features Useful as both a teaching resource and as a practical tool for professional investors. Ideal textbook for first year graduate students in quantitative finance programs, such as those in master’s programs in Mathematical Finance, Quant Finance or Financial Engineering. Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning. Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432.
Quantitative Fund Management
by M. A. H. Dempster, Georg Pflug, and Gautam MitraThe First Collection That Covers This Field at the Dynamic Strategic and One-Period Tactical Levels. Addressing the imbalance between research and practice, Quantitative Fund Management presents leading-edge theory and methods, along with their application in practical problems encountered in the fund management industry. A Current Snapshot of State-of-the-Art Applications of Dynamic Stochastic Optimization Techniques to Long-Term Financial Planning - The first part of the book initially looks at how the quantitative techniques of the equity industry are shifting from basic Markowitz mean-variance portfolio optimization to risk management and trading applications. This section also explores novel aspects of lifetime individual consumption investment problems, fixed-mix portfolio rebalancing allocation strategies, debt management for funding mortgages and national debt, and guaranteed return fund construction. Up-to-Date Overview of Tactical Financial Planning and Risk Management - The second section covers nontrivial computational approaches to tactical fund management. This part focuses on portfolio construction and risk management at the individual security or fund manager level over the period up to the next portfolio rebalance. It discusses non-Gaussian returns, new risk-return tradeoffs, and the robustness of benchmarks and portfolio decisions. The Future Use of Quantitative Techniques in Fund Management - With contributions from well-known academics and practitioners, this volume will undoubtedly foster the recognition and wider acceptance of stochastic optimization techniques in financial practice.
Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling
by Y. Z. MaEarth science is becoming increasingly quantitative in the digital age. Quantification of geoscience and engineering problems underpins many of the applications of big data and artificial intelligence. This book presents quantitative geosciences in three parts. Part 1 presents data analytics using probability, statistical and machine-learning methods. Part 2 covers reservoir characterization using several geoscience disciplines: including geology, geophysics, petrophysics and geostatistics. Part 3 treats reservoir modeling, resource evaluation and uncertainty analysis using integrated geoscience, engineering and geostatistical methods. As the petroleum industry is heading towards operating oil fields digitally, a multidisciplinary skillset is a must for geoscientists who need to use data analytics to resolve inconsistencies in various sources of data, model reservoir properties, evaluate uncertainties, and quantify risk for decision making. This book intends to serve as a bridge for advancing the multidisciplinary integration for digital fields. The goal is to move beyond using quantitative methods individually to an integrated descriptive-quantitative analysis. In big data, everything tells us something, but nothing tells us everything. This book emphasizes the integrated, multidisciplinary solutions for practical problems in resource evaluation and field development.
Quantitative Graph Theory: Mathematical Foundations and Applications
by Matthias Dehmer Frank Emmert-StreibThe first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathematical Foundations and Applications presents and demonstrates existing and novel methods for analyzing graphs quantitatively. Incorporating interdisciplinary knowledge from graph theory, information theory, measurement theory, and statistical technique
Quantitative Investigations in the Biosciences using MINITAB
by John EddisonUntil recently, acquiring a background in the basic methodological principles that apply to most types of investigations meant struggling to obtain results through laborious calculations. The advent of statistical software packages has removed much of the tedium and many of the errors of manual calculations and allowed a marked increase in the depth and sophistication of analyses. Although most statistics classes now incorporate some instruction in using a statistics package, most introductory texts do not.Quantitative Investigations in the Biosciences using MINITAB fills this void by providing an introduction to investigative methods that, in addition to outlining statistical principles and describing methods of calculations, also presents essential commands and interprets output from the statistics package MINITAB.The author introduces the three basic elements of investigations-design, analysis, and reporting-using an extremely accessible approach that keeps mathematical detail to a minimum. He groups statistical tests according to the type of problem they are used to examine, such as comparisons, sequential relationships, and associations.Quantitative Investigations in the Biosciences using MINITAB draws techniques and examples from a variety of subjects, ranging from physiology and biochemistry through to ecology, behavioral sciences, medicine, agriculture and horticulture, and complements the mathematical results with formal conclusions for all of the worked examples. It thus provides an ideal handbook for anyone in virtually any field who wants to apply statistical techniques to their investigations.
Quantitative Investing: From Theory to Industry
by Lingjie MaThis book provides readers with a systematic approach to quantitative investments and bridges the gap between theory and practice, equipping students to more seamlessly enter the world of industry. A successful quantitative investment strategy requires an individual to possess a deep understanding of the financial markets, investment theories and econometric modelings, as well as the ability to program and analyze real-world data sets. In order to connect finance theories and practical industry experience, each chapter begins with a real-world finance case study. The rest of the chapter introduces fundamental insights and theories, and teaches readers to use statistical models and R programming to analyze real-world data, therefore grounding the learning process in application. Additionally, each chapter profiles significant figures in investment and quantitative studies, so that readers can more fully understand the history of the discipline. This volume will be particularly useful to advanced students and practitioners in finance and investments.
Quantitative Literacy
by Bruce C. Crauder Benny Evans Jerry A. Johnson Alan V. Noell"I finally understand why I need to learn some math!" says a student after finishing a course that used Quantitative Literacy. That enthusiastic response gets to the heart of how this remarkable textbook works. Quantitative Literacy shows students that they use math in their everyday lives more than they realize, and that learning math in real-world contexts not only makes it easier to get better grades, but prepares them for decisions they'll face about money, voting and politics, health issues, and much more. The authors draw on a wide range of examples to give students basic mathematical tools-- from sports to personal finance to sociopolitical action to medical tests to the arts--with coverage that neatly balances discussions of ideas with computational practice.
Quantitative Literacy Through Games and Gambling (Textbooks in Mathematics)
by Mark HunacekThis book was developed to address a need. Quantitative Literacy courses have been established in the mathematics curriculum for decades now. The students in these courses typically dislike and fear mathematics, and the result is often a class populated by many students who are unmotivated and uninterested in the material. This book is a text for such a course; however, it is focused on a single idea that most students seem to already have some intrinsic interest in and is written at an accessible level. It covers the basic ideas of discrete probability and shows how these ideas can be applied to familiar games (roulette, poker, blackjack, etc.). The gambling material is interweaved through the book and introduced as soon as the necessary mathematics has been developed. Throughout, mathematical formalism and symbolism have been avoided, and numerous examples are provided. The book starts with a simple definition of probability, goes through some basic concepts like combining events and expected value, and then discusses some elementary mathematical aspects of various games. Roulette is introduced very early on, as is the game of craps, which requires some knowledge of conditional probability. Other games like poker, blackjack, and lotteries, whose study requires some rudimentary combinatorics, come shortly thereafter. The book ends with a brief introduction to zero-sum games, with some attention paid to the use of these ideas in studying bluffing. In addition to discussion of these traditional games, the author motivates probability by talking about a few applications in legal proceedings that illustrate how mathematics has been misused in the courtroom. There is also a discussion of the Monty Hall problem, a nonintuitive result in probability that has an interesting and colorful history. Hopefully, students studying from this text will find that mathematics is not as horrible as they have always thought and offers some interesting applications in the real world. This should perhaps be the goal of any quantitative literacy course.
Quantitative Methoden 1: Einführung in die Statistik für Psychologen und Sozialwissenschaftler (Springer-Lehrbuch)
by Björn Rasch Malte Friese Wilhelm Hofmann Ewald NaumannWelche Angst plagt die meisten Studienanfänger im Psychologie-Studium? Die Angst vor der Statistik-Prüfung! Hier schaffen wir Abhilfe, denn die Statistik ist ein wichtiges Handwerkszeug, um zu verstehen, wie die Psychologie Erkenntnisse gewinnt und ihre Forschungsergebnisse zu bewerten sind – und wenn die Statistik verständlich erklärt ist, gibt es keinen Grund zur Panik! Mit den beiden Bänden Quantitative Methoden 1/2 meistern Sie die Grundlagen der Statistik! Anwendungsbezogen und verständlich werden hier die Inhalte der Vorlesungen Quantitative Methoden, Statistik oder Methodenlehre erklärt. Band 1 umfasst die Themen deskriptive Statistik, Grundzüge der Inferenzstatistik und den t-Test sowie Zusammenhangsmaße und Regression. Mit Verständnisfragen und Antworten, Glossar der wichtigsten Statistik-Begriffe und Verteilungstabellen. – Außerdem mit vielen kostenlosen Zusatzmaterialien auf der begleitenden Lehrbuch-Website: Mehrere hundert Extraseiten mit Anleitungen zur konkreten Durchführung der behandelten statistischen Verfahren mit SPSS und R, Informationen zur Durchführung von Teststärkeanalysen und Stichprobenumfangsplanungen mit G*Power sowie Beispielaufgaben – alles inklusive notwendiger Datensätze. Und ganz NEU in der 4. Auflage: Zahlreiche Erklärungsvideos zu wichtigen Formeln und Zusammenhängen!
Quantitative Methoden 1: Einführung in die Statistik für Psychologie, Sozial- & Erziehungswissenschaften
by Björn Rasch Malte Friese Wilhelm Hofmann Ewald NaumannDieses Lehrbuch macht Dich fit für die Statistik-Prüfung – hier geht es um die Deskriptive Statistik sowie um die ersten Schritte in Inferenzstatistik, z.B. den t-Test. Also Dinge, die in vielen sozialwissenschaftlichen Studiengängen, wie z.B. Psychologie, Soziologie oder Erziehungswissenschaften, auf dem Lehrplan stehen. Vielen macht die Statistik Angst – aber mit diesem Buch wirst Du die Prüfung meistern, weil Dir hier alles sehr verständlich und ergänzt durch kostenfreie Videos und umfangreiche zusätzliche Materialien erklärt wird.
Quantitative Methoden 2: Einführung in die Statistik für Psychologie, Sozial- & Erziehungswissenschaften
by Wilhelm Hofmann Björn Rasch Malte Friese Ewald NaumannDieses Lehrbuch macht Dich fit für die Statistik-Prüfung – hier geht es u.a. um Varianzanalysen und Verfahren für Rang- und Nominaldaten. Also Dinge, die in vielen sozialwissenschaftlichen Studiengängen, wie z.B. Psychologie, Soziologie oder Erziehungswissenschaften, auf dem Lehrplan stehen. Mit diesem Buch wirst Du die Prüfung meistern, weil Dir hier alles sehr verständlich und ergänzt durch kostenfreie Videos und umfangreiche zusätzliche Materialien erklärt wird.
Quantitative Methods
by Paolo BrandimarteAn accessible introduction to the essential quantitative methods for making valuable business decisionsQuantitative methods-research techniques used to analyze quantitative data-enable professionals to organize and understand numbers and, in turn, to make good decisions. Quantitative Methods: An Introduction for Business Management presents the application of quantitative mathematical modeling to decision making in a business management context and emphasizes not only the role of data in drawing conclusions, but also the pitfalls of undiscerning reliance of software packages that implement standard statistical procedures. With hands-on applications and explanations that are accessible to readers at various levels, the book successfully outlines the necessary tools to make smart and successful business decisions.Progressing from beginner to more advanced material at an easy-to-follow pace, the author utilizes motivating examples throughout to aid readers interested in decision making and also provides critical remarks, intuitive traps, and counterexamples when appropriate.The book begins with a discussion of motivations and foundations related to the topic, with introductory presentations of concepts from calculus to linear algebra. Next, the core ideas of quantitative methods are presented in chapters that explore introductory topics in probability, descriptive and inferential statistics, linear regression, and a discussion of time series that includes both classical topics and more challenging models. The author also discusses linear programming models and decision making under risk as well as less standard topics in the field such as game theory and Bayesian statistics. Finally, the book concludes with a focus on selected tools from multivariate statistics, including advanced regression models and data reduction methods such as principal component analysis, factor analysis, and cluster analysis.The book promotes the importance of an analytical approach, particularly when dealing with a complex system where multiple individuals are involved and have conflicting incentives. A related website features Microsoft Excel® workbooks and MATLAB® scripts to illustrate concepts as well as additional exercises with solutions.Quantitative Methods is an excellent book for courses on the topic at the graduate level. The book also serves as an authoritative reference and self-study guide for financial and business professionals, as well as readers looking to reinforce their analytical skills.
Quantitative Methods for HIV/AIDS Research (Chapman & Hall/CRC Biostatistics Series)
by Cliburn Chan Michael G. Hudgens Shein-Chung ChowQuantitative Methods in HIV/AIDS Research provides a comprehensive discussion of modern statistical approaches for the analysis of HIV/AIDS data. The first section focuses on statistical issues in clinical trials and epidemiology that are unique to or particularly challenging in HIV/AIDS research; the second section focuses on the analysis of laboratory data used for immune monitoring, biomarker discovery and vaccine development; the final section focuses on statistical issues in the mathematical modeling of HIV/AIDS pathogenesis, treatment and epidemiology. This book brings together a broad perspective of new quantitative methods in HIV/AIDS research, contributed by statisticians and mathematicians immersed in HIV research, many of whom are current or previous leaders of CFAR quantitative cores. It is the editors’ hope that the work will inspire more statisticians, mathematicians and computer scientists to collaborate and contribute to the interdisciplinary challenges of understanding and addressing the AIDS pandemic.
Quantitative Methods for Investigating Infectious Disease Outbreaks (Texts in Applied Mathematics #70)
by Ping Yan Gerardo ChowellThis book provides a systematic treatment of the mathematical underpinnings of work in the theory of outbreak dynamics and their control, covering balanced perspectives between theory and practice including new material on contemporary topics in the field of infectious disease modelling. Specifically, it presents a unified mathematical framework linked to the distribution theory of non-negative random variables; the many examples used in the text, are introduced and discussed in light of theoretical perspectives. The book is organized into 9 chapters: The first motivates the presentation of the material on subsequent chapters; Chapter 2-3 provides a review of basic concepts of probability and statistical models for the distributions of continuous lifetime data and the distributions of random counts and counting processes, which are linked to phenomenological models. Chapters 4 focuses on dynamic behaviors of a disease outbreak during the initial phase while Chapters 5-6 broadly cover compartment models to investigate the consequences of epidemics as the outbreak moves beyond the initial phase. Chapter 7 provides a transition between mostly theoretical topics in earlier chapters and Chapters 8 and 9 where the focus is on the data generating processes and statistical issues of fitting models to data as well as specific mathematical epidemic modeling applications, respectively. This book is aimed at a wide audience ranging from graduate students to established scientists from quantitatively-oriented fields of epidemiology, mathematics and statistics. The numerous examples and illustrations make understanding of the mathematics of disease transmission and control accessible. Furthermore, the examples and exercises, make the book suitable for motivated students in applied mathematics, either through a lecture course, or through self-study. This text could be used in graduate schools or special summer schools covering research problems in mathematical biology.
Quantitative Methods for Management: A Practical Approach
by Miguel Ángel Canela Inés Alegre Alberto IbarraThis book focuses on the use of quantitative methods for both business and management, helping readers understand the most relevant quantitative methods for managerial decision-making. Pursuing a highly practical approach, the book reduces the theoretical information to a minimum, so as to give full prominence to the analysis of real business problems.Each chapter includes a brief theoretical explanation, followed by a real-life managerial case that needs to be solved, which is accompanied by a corresponding Microsoft Excel® dataset. The practical cases and exercises are solved using Excel, and for each problem, the authors provide an Excel file with the complete solution and corresponding calculations, which can be downloaded easily from the book’s website. Further, in an appendix, readers can find solutions to the same problems, but using the R statistical language.The book represents a valuable reference guide for postgraduate, MBA and executive education students, as it offers a hands-on, practical approach to learning quantitative methods in a managerial context. It will also be of interest to managers looking for a practical and straightforward way to learn about quantitative methods and improve their decision-making processes.
Quantitative Methods for Precision Medicine: Pharmacogenomics in Action (Chapman & Hall/CRC Biostatistics Series)
by Rongling WuModern medicine is undergoing a paradigm shift from a "one-size-fits-all" strategy to a more precise patient-customized therapy and medication plan. While the success of precision medicine relies on the level of pharmacogenomic knowledge, dissecting the genetic mechanisms of drug response in a sufficient detail requires powerful computational tools. Quantitative Methods for Precision Medicine: Pharmacogenomics in Action presents the advanced statistical methods for mapping pharmacogenetic control by integrating pharmacokinetic and pharmacodynamic principles of drug-body interactions. Beyond traditional reductionist-based statistical genetic approaches, statistical formulization in this book synthesizes elements of multiple disciplines to infer, visualize, and track how pharmacogenes interact together as an intricate but well-coordinated system to mediate patient-specific drug response.Features: Functional and systems mapping models to characterize the genetic architecture of multiple medication processes Statistical methods for analyzing informative missing data in pharmacogenetic association studies Functional graph theory of inferring genetic interaction networks from association data Leveraging the concept of epistasis to capture its bidirectional, signed and weighted properties Modeling gene-induced cell-cell crosstalk and its impact on drug response A graph model of drug-drug interactions in combination therapies Critical methodological issues to improve pharmacogenomic research as the cornerstone of precision medicine This book is suitable for graduate students and researchers in the fields of biology, medicine, bioinformatics and drug design and delivery who are interested in statistical and computational modelling of biological processes and systems. It may also serve as a major reference for applied mathematicians, computer scientists, and statisticians who attempt to develop algorithmic tools for genetic mapping, systems pharmacogenomics and systems biology. It can be used as both a textbook and research reference. Professionals in pharmaceutical sectors who design drugs and clinical doctors who deliver drugs will also find it useful.
Quantitative Methods for the Social Sciences: A Practical Introduction with Examples in SPSS and Stata
by Daniel StockemerThis textbook offers an essential introduction to survey research and quantitative methods. Building on the premise that statistical methods need to be learned in a practical fashion, the book guides students through the various steps of the survey research process and helps to apply those steps toward a real example. In detail, the textbook introduces students to the four pillars of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. Students are shown how to create their own questionnaire based on some theoretically derived hypotheses to achieve empirical findings for a solid dataset. Lastly, they use said data to test their hypotheses in a bivariate and multivariate realm. The book explains the theory, rationale and mathematical foundations of these tests. In addition, it provides clear instructions on how to conduct the tests in SPSS and Stata. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research or quantitative methods classes in the social sciences.
Quantitative Methods for the Social Sciences: A Practical Introduction with Examples in R (Springer Texts in Political Science and International Relations)
by Daniel Stockemer Jean-Nicolas BordeleauThis textbook offers an essential introduction to survey research and quantitative methods with clear instructions on how to conduct statistical tests with R. Building on the premise that we need to teach statistical methods in a holistic and practical format, the book guides students through the four main elements of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. In detail, students will learn how to create their own questionnaire on the basis of formulating hypotheses; sampling participants; disseminating their questionnaire; creating datasets; and analyzing their data. The data analytical sections of this revised and extended edition explain the theory, rationale and mathematical foundations of relevant bivariate and multi-variate statistical tests. These include the T-test, F-test, Chi-square test and correlation analyses, as well as bivariate and multivariate regression analyses. In addition, the book offers a brief introduction to statistical computing with R, which includes clear instructions on how to conduct these statistical tests in R. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research and quantitative methods classes in the social sciences.
Quantitative Methods for Traditional Chinese Medicine Development (Chapman And Hall/crc Biostatistics Ser.)
by Shein-Chung ChowA Western-Based Approach to Analyzing TCMsIn recent years, many pharmaceutical companies and clinical research organizations have been focusing on the development of traditional Chinese (herbal) medicines (TCMs) as alternatives to treating critical or life-threatening diseases and as pathways to personalized medicine.Quantitative Methods for Tradit
Quantitative Methods in Demography: Methods and Related Applications in the Covid-19 Era (The Springer Series on Demographic Methods and Population Analysis #52)
by Christos H. Skiadas Charilaos SkiadasThis book provides quantitative and applied methodologies in the Covid-19 era exploring important issues in demography, population studies, and health. It provides insight into health and health measures as to the healthy life years lost and the healthy life expectancy related to Covid-19 pandemic. It also describes mortality and survival and focuses on data analysis in demography and population studies. Special methods and applications in demography and society are also described, thereby including applications in society, pension and insurance. As such, this book is a valuable guide for researchers, theoreticians and practitioners from various scientific fields.
Quantitative Methods in Finance: Exploring the Drivers of Sustainable Economic Growth in the EU (Sustainable Finance)
by Ştefan Cristian GherghinaThis book explores certain social and environmental drivers of sustainable economic growth for European Union countries (EU-27) and United Kingdom (UK) in the context of the UN 2030 Agenda for Sustainable Development. The author provides a comprehensive overview of the factors that impact and facilitate sustainable economic growth and discusses the complex set of factors involved in sustainable economic development. Special attention is given to quantitative frameworks and empirical modelling, with the main focus on panel data regression models and vector error correction model approach. Furthermore, the book develops ratings of sustainable economic growth for each of the explored countries, by employing data mining techniques such as principal component analysis. Also, the data envelopment analysis non-parametric methodology towards assessing sustainable economic growth is investigated, as well as the cluster analysis in order to classify the selected nations according to sustainable economic growth. The book appeals to policy-makers and academics targeting to learn more about the characteristics of sustainable economic growth.
Quantitative Methods in Pharmaceutical Research and Development: Concepts and Applications
by Olga V. Marchenko Natallia V. KatenkaThis contributed volume presents an overview of concepts, methods, and applications used in several quantitative areas of drug research, development, and marketing. Chapters bring together the theories and applications of various disciplines, allowing readers to learn more about quantitative fields, and to better recognize the differences between them. Because it provides a thorough overview, this will serve as a self-contained resource for readers interested in the pharmaceutical industry, and the quantitative methods that serve as its foundation. Specific disciplines covered include:BiostatisticsPharmacometricsGenomicsBioinformaticsPharmacoepidemiologyCommercial analyticsOperational analyticsQuantitative Methods in Pharmaceutical Research and Development is ideal for undergraduate students interested in learning about real-world applications of quantitative methods, and the potential career options open to them. It will also be of interest to experts working in these areas.
Quantitative Methods in Transportation
by Dušan Teodorović Miloš NikolićQuantitative Methods in Transportation provides the most useful, simple, and advanced quantitative techniques for solving real-life transportation engineering problems. It aims to help transportation engineers and analysts to predict travel and freight demand, plan new transportation networks, and develop various traffic control strategies that are safer, more cost effective, and greener. Transportation networks can be exceptionally large, and this makes many transportation problems combinatorial, and the challenges are compounded by the stochastic and independent nature of trip-planners decision making. Methods outlined in this book range from linear programming, multi-attribute decision making, data envelopment analysis, probability theory, and simulation to computer techniques such as genetic algorithms, simulated annealing, tabu search, ant colony optimization, and bee colony optimization. The book is supported with problems and has a solutions manual to aid course instructors.