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International Series in Operations Research & Management Science

Machine Learning Technologies on Energy
Economics and Finance

Machine Learning Technologies on Energy Economics and Finance

Energy and Sustainable Analytics, Volume 1

Cases and Studies in Using Operations Research and Management Science Methods

Outsourcing

Energy and Sustainable Analytics, Volume 2

Innovation at the Interface

University-Industry Collaboration

From Theory to Practice

Outsourcing Using Operations Research and Management Science Methods

Challenges in Economics and Management Science

The Unaffordable Price of Static Decision-making Models

Applications to Large-Scale Engineering Problems

Optimization via Relaxation and Decomposition

This book highlights the major features of the ripple effect and introduces methodologies to mitigate its adverse impact on supply chain resilience and to recover from severe disruptions. It brings fresh insights into the fields of supply chain management and engineering, addressing three fundamental questions: “In what circumstance does one failure trigger others?” “Which supply chain structures are especially susceptible to the ripple effect?” “What are the typical ripple effect scenarios and the most efficient ways to respond to them?”In this new edition, recent advancements are incorporated, particularly in areas such as supply chain viability, digital supply chains, artificial intelligence, and epidemiological models. Furthermore, it introduces new methodologies with a particular emphasis on data-driven and AI-based approaches.This comprehensive book provides innovative optimization and simulation models to address real-world challenges. With examples from industrial and service sectors, it offers actionable decision-making recommendations for tackling disruption risks in the supply chain proactively and reactively. As such the book is a comprehensive source for diverse readerships.

Handbook of Ripple Effects in the Supply Chain

This book presents a comprehensive series of methods in nonsmooth optimization, with a particular focus on their application in stochastic programming and dedicated algorithms for decision-making under uncertainty. Each method is accompanied by rigorous mathematical analysis, ensuring a deep understanding of the underlying principles. The theoretical discussions included are essential for comprehending the mechanics of various algorithms and the nature of the solutions they provide-whether they are global, local, stationary, or critical. The book begins by introducing fundamental tools from set-valued analysis, optimization, and probability theory. It then transitions from deterministic to stochastic optimization, starting with a thorough discussion of modeling, understanding uncertainty, and incorporating it into optimization problems. Following this foundation, the book explores numerical algorithms for nonsmooth optimization, covering well-known decomposition techniques and algorithms for convex optimization, mixed-integer convex programming, and nonconvex optimization. Additionally, it introduces numerical algorithms specifically for stochastic programming, focusing on stochastic programming with recourse, chance-constrained optimization, and detailed algorithms for both risk-neutral and risk-averse multistage stochastic programs.

The book guides readers through the entire process, from defining optimization models for practical problems to presenting implementable algorithms that can be applied in practice. It is intended for students, practitioners, and scholars who may be unfamiliar with stochastic programming and nonsmooth optimization. The analyses provided are also valuable for practitioners who may not be interested in convergence proofs but wish to understand the nature of the solutions obtained.

From Conceptual Algorithms to Real-World Applications

Methods of Nonsmooth Optimization in Stochastic Programming

This book demonstrates how decision-making models can be applied to solve specific real-life problems, with a particular emphasis on wind energy. In a step-by-step manner, it guides the reader through decision-making, the formulation of optimization models, and the methods for solving them. After providing an overview of various models for the design of wind farms, it presents an optimization model for deciding which economy (country) to invest in and models for selecting suppliers. A dedicated chapter focuses on different models for monitoring and predictive maintenance for wind turbines (farms) due to the construction of turbine blades and vibration. It shows how combinatorial optimization models can help to make optimal decisions for one-dimensional cutting stock of blanks, their processing, and determining the optimal composition for production. Moreover, it discusses how the energy consumption balance index formed by conventional and renewable sources can be determined and presents a means of identifying the relative share of wind energy consumption among the other renewable sources.&nbsp;Operations research professionals, students, and decision-makers alike will find this book to be a valuable resource for tackling real-world challenges and driving sustainable advances in wind energy solutions.

This book demonstrates how decision-making models can be applied to solve specific real-life problems, with a particular emphasis on wind energy. In a step-by-step manner, it guides the reader through decision-making, the formulation of optimization models, and the methods for solving them. After providing an overview of various models for the design of wind farms, it presents an optimization model for deciding which economy (country) to invest in and models for selecting suppliers. A dedicated chapter focuses on different models for monitoring and predictive maintenance for wind turbines (farms) due to the construction of turbine blades and vibration. It shows how combinatorial optimization models can help to make optimal decisions for one-dimensional cutting stock of blanks, their processing, and determining the optimal composition for production. Moreover, it discusses how the energy consumption balance index formed by conventional and renewable sources can be determined and presents a means of identifying the relative share of wind energy consumption among the other renewable sources.&nbsp;Operations research professionals, students, and decision-makers alike will find this book to be a valuable resource for tackling real-world challenges and driving sustainable advances in wind energy solutions.

Decision-Making in Design, Maintenance, Planning, and Investment of Wind Energy

This book examines multiple criteria decision making (MCDM) and presents the Sequential Iterative Modelling for Urban Systems (SIMUS) as a method to be used for strategic decision making. It emphasizes the necessity to take into account aspects related to real world scenarios and incorporating possible real-life aspects for modelling. The book also highlights the use of sensitivity analysis and presents a method for using criteria marginal values instead of weights, which permits the drawing of curves that depicts the variations of the objective function due to increments/decrements of criteria values. In this way, it also gives quantitative values of the objective function allowing stakeholders to perform a comprehensive risk analysis for a solution when it is affected by exogenous variables.&nbsp;Strategic Multi-Criteria Decision Making: A Practical Guide for Complex Scenarios is divided into four parts. Part 1 is devoted to exploring the history and development of the discipline and the way it is currently used. It highlights drawbacks and problems that scholars have identified in different MCDM methods and techniques. Part 2 refers to what can be done using the MCDM process. Part 3 proposes the SIMUS method as a strategic procedure to deal with MCDM problems, and addressing how to approach complicate scenarios. Part 4 is entirely devoted to support practitioners through more than 100 questions a user may ask, and their corresponding answers, as well as a collection of solved six complex real-life scenarios. The decision-making process can be a complex task, especially with multi-criteria problems. With large amounts of information, it can be an extremely difficult to make a rational decision, due to the number of intervening variables, their interrelationships, potential solutions that might exist, diverse objectives envisioned for a project, etc. The SIMUS method has been designed to offer a strategy to help organize, classify, and evaluate this information effectively.

This book examines multiple criteria decision making (MCDM) and presents the Sequential Iterative Modelling for Urban Systems (SIMUS) as a method to be used for strategic decision making. It emphasizes the necessity to take into account aspects related to real world scenarios and incorporating possible real-life aspects for modelling. The book also highlights the use of sensitivity analysis and presents a method for using criteria marginal values instead of weights, which permits the drawing of curves that depicts the variations of the objective function due to increments/decrements of criteria values. In this way, it also gives quantitative values of the objective function allowing stakeholders to perform a comprehensive risk analysis for a solution when it is affected by exogenous variables.&nbsp;Strategic Multi-Criteria Decision Making: A Practical Guide for Complex Scenarios is divided into four parts. Part 1 is devoted to exploring the history and development of the discipline and the way it is currently used. It highlights drawbacks and problems that scholars have identified in different MCDM methods and techniques. Part 2 refers to what can be done using the MCDM process. Part 3 proposes the SIMUS method as a strategic procedure to deal with MCDM problems, and addressing how to approach complicate scenarios. Part 4 is entirely devoted to support practitioners through more than 100 questions a user may ask, and their corresponding answers, as well as a collection of solved six complex real-life scenarios. The decision-making process can be a complex task, especially with multi-criteria problems. With large amounts of information, it can be an extremely difficult to make a rational decision, due to the number of intervening variables, their interrelationships, potential solutions that might exist, diverse objectives envisioned for a project, etc. The SIMUS method has been designed to offer a strategy to help organize, classify, and evaluate this information effectively.

A Practical Guide for Complex Scenarios

Strategic Approach in Multi-Criteria Decision Making

This book applies Multicriteria Decision Making (MCDM) tools and techniques to problems in location analysis. It begins with a generic model for MCDM and subsequently develops specific versions of the technique for particular location problems. Throughout the book, MCDM is understood to encompass all tools and techniques that choose or rank existing or feasible solutions, including discrete multi-attribute decision making (MADM) problems, which typically include an attribute table that specifies the consequences of each decision with regard to the given criteria, as well as multi-objective linear problems (MOLPs), which incorporate all objectives in a single optimization problem.&nbsp; 

The book is organized as follows: the first four chapters introduce readers to the basic tools and techniques used in single-objective optimization, multicriteria decision making, location analysis, and other tools, such as statistical regression and geographical information systems. This is followed by ten chapters on model applications, each of which introduces readers to a specific location problem and applies one technique to solve it. The book is then wrapped up in a closing chapter that looks at the location process from a practitioner’s point of view.&nbsp; This book is intended as a textbook for upper-undergraduate and master-level courses on location analysis. It will also benefit decision-makers who actually need to locate facilities.&nbsp;

First book to fully incorporate MCDM techniques with location analysis Tailors specific techniques to particular location problemsEiselt and Marianov are two of the best known scholars/authors in the field

Multicriteria Location Analysis

This book brings Data Envelopment Analysis (DEA) based techniques and big data together to explore the novel uses and potentials of DEA under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.&nbsp;Over the past four decades, DEA models have been applied in almost every major field of study. However, DEA has not been used to its fullest extent. As the inter- and intra-disciplinary research grows, DEA could be used in potentially many other ways; for instance, DEA could be viewed as a data mining tool for data-enabled analytics. One opportunity is brought by the existence of big data. Although big data has existed for a while now, gaining popularity among insight seekers, we are still in incipientstages when it comes to taking full advantage of its potential. Generally, researchers have either been interested in examining its origin or in developing and using big data technology.As the amount of (big) data is growing every day in an exponential manner, so does its complexity; in this sense, various types of data are surfacing, whose study and examination could shed new light on phenomena of interest. A quick review of existing literature shows that big data is a new entrant within the DEA framework. Recently, there has been an increasing interest in bringing the two concepts together, with research studies aiming to integrate DEA and big data concepts within a single framework. But, more work is needed to fully explore the value of their intersection—it is time to view DEA in light of its potential usage in new fields or new usage within the existing fields, under the big data umbrella. It is time to view DEA models beyond their present scope and mine new insights for better data-driven decision-making.

This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

DEA for Big Data

Data-Enabled Analytics

The Omega Series

This book is based on the underlying premise that much can be learned from contemporary thinking about the treatment of complexity, uncertainty, risk-taking and the importance of context in decision making for planning, in fields where these concepts have long been deployed in complex problem-solving. It explores the sophisticated theoretical approaches which have been developed in order to analyse the issues surrounding that complexity. In so doing, the book discusses the overriding influence of complexity theory on the whole field of risk and uncertainty as it impacts on all stages of the project life-cycle. It furthermore examines various decision-support methods, tools and techniques that have been developed and employed by different professions and disciplines with the aim of addressing risk, uncertainty and complexity in planning in a range of different contexts. The book especially explores the parameters of these different contexts and their characteristics in an effort to identify both generic and context-specific lessons that may be of value to planning exercises for Mega Transport Projects.

This book is based on the underlying premise that much can be learned from contemporary thinking about the treatment of complexity, uncertainty, risk-taking and the importance of context in decision making for planning, in fields where these concepts have long been deployed in complex problem-solving. It explores the sophisticated theoretical approaches which have been developed in order to analyse the issues surrounding that complexity. In so doing, the book discusses the overriding influence of complexity theory on the whole field of risk and uncertainty as it impacts on all stages of the project life-cycle. It furthermore examines various decision-support methods, tools and techniques that have been developed and employed by different professions and disciplines with the aim of addressing risk, uncertainty and complexity in planning in a range of different contexts. The book especially explores the parameters of these different contexts and their characteristics in an effort to identify both generic and context-specific lessons that may be of value to planning exercises for Mega Transport Projects.

Planning, Appraisal and Delivery of Infrastructure Mega Projects 2: An Interdisciplinary Approach to Risk, Uncertainty and Complexity

Understand the complexities involved in managing destinations, including the current challenges at the forefront of the tourism industry such as climate change, overtourism and crisis management.

A Practical Approach

Responsible Destination Management

De Gruyter Series in Measurement Sciences

Advances and Applications

Artificially Intelligent Sensing

Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming

Using SAS Enterprise Miner

Data Science and Machine Learning for Non-Programmers

Learn how to plan, design and deliver sustainable events, while considering and measuring the long-term impacts to meet the triple bottom line (TBL) of people, planet and profit.

Planning, Designing and Delivering

Sustainability in Events Management

Dunes of the World

Dunes of China

Using Sustainability to Drive Growth

Competitive Sustainability

Dieses Buch stellt aktuelle und neuartige Methoden für die Arbeit der Revision sowie für Prüfungen und Tests von IT-Systemen vor. Berücksichtigt werden dabei Aspekte des Datenschutzes, der Cybersicherheit sowie der Effektivität und Funktionalität von IT- und KI-Systemen. Mit Beiträgen von Irfan Altiok, Nikolas Becker, Anna Cardillo, Karina Filusch, Frank Fünfstück, Stefan Marienfeld, Bernhard Waltl und Daniela Will.Der Inhalt<ul><li>Datenschutz-Managementsystem 2.0 inkl. Reifegradmodell</li><li>Meldepflichten für Sicherheitsvorfälle und Datenpannen</li><li>Datenschutzrechtliche Dienstleisterkontrolle</li><li>Prüfung von IT-Outsourcing und Cloud-Computing</li><li>Assessments mittels Red Teaming nach dem Assume-Breach-Ansatz</li><li>Internes und externes Audit von KI-Systemen</li></ul>Die Zielgruppen<ul><li>Prüfer, Revisoren, IT-Auditoren</li><li>Datenschutzbeauftragte, Datenschutzkoordinatoren,&nbsp;Datenschutzauditoren sowie Beschäftigte und Verantwortliche in Datenschutzfunktionen</li><li>IT-Compliance-Manager,&nbsp;IT-Sicherheitsbeauftragte, CISOs,&nbsp;IT-Verantwortliche</li><li>KI-Beauftragte</li></ul>Die HerausgeberinDr. Aleksandra Sowa ist zertifizierte Datenschutzbeauftragte (DSB-TÜV), Datenschutz- auditorin&nbsp; (DSA-TÜV),&nbsp; IT-Compliance-Managerin&nbsp; (ITCM)&nbsp; und&nbsp; IT Information&nbsp; Security Practitioner (ITISP). Sie war für den Vorstand Datenschutz, Recht und Compliance (DRC) der Deutschen Telekom AG tätig, ist Sachverständige für IT-Sicherheit im Innenausschuss des Bundestages und leitete zusammen mit dem deutschen Kryptologen Hans Dobbertin das Horst Görtz Institut für Sicherheit in der Informationstechnik. Aleksandra Sowa ist Publizistin und Buchautorin.&nbsp;

Dieses Buch stellt aktuelle und neuartige Methoden für die Arbeit der Revision sowie für Prüfungen und Tests von IT-Systemen vor. Berücksichtigt werden dabei Aspekte des Datenschutzes, der Cybersicherheit sowie der Effektivität und Funktionalität, und es werden Ansätze für Datenschutzbeauftragte, Sicherheitsbeauftragte, CISOs, Compliance-Manager, KI-Beauftragte etc. vorgestellt.

Neue Ansätze für die IT-Revision

IT-Prüfung, Datenschutzmanagement und KI-Audit

The Extraordinary Story of the Bishnoi, the World’s First Eco-Warriors

My Head For A Tree

Learn how to manage the risks and opportunities of agentic AI with this practical guide to ensuring the safe and beneficial developments of advanced AI systems.

Principles and Responsible Practices

Safer Agentic AI

Nachhaltige Energiespeicher - ein kompakter Einstieg für Studierende und Ingenieure Energiespeicher sind ein essentieller Bestandteil von Energiesystemen, um eine verlässliche Energieversorgung zu gewährleisten. Dies gilt insbesondere für erneuerbare Energien. Dabei sollen die Speichertechnologien selbst der Nachhaltigkeit nicht entgegenstehen. Dieses Buch richtet sich an Studierende der Elektro-, Umwelt- und Energietechnik sowie F&amp;E-Ingenieure, die vor der Herausforderung stehen, umweltverträgliche Energiespeicher zu entwickeln, die zugleich wirtschaftlich rentabel und gesellschaftlich akzeptiert sind. Ausgehend von den physikalisch-chemischen Grundlagen der verschiedenen Speichertechnologien werden Funktionsweise, Anwendung und Komponenten folgender Speichersysteme erläutert: - Mechanische Energiespeicher: Pumpspeicher, Druckluftspeicher - Chemische Energiespeicher: Wasserstofftechnik, Methanisierung, biogene und synthetische Kraftstoffe - Elektrochemische Energiespeicher: Batterien und Akkumulatoren, Brennstoffzellen und Redox-Flow-Systeme - Thermische Energiespeicher: sensible Wärmespeicher, Latentwärmespeicher, Sorptionsspeicher Neben den funktionalen Zusammenhängen werden die ökologischen, ökonomischen und sozialen Aspekte der Speichertechnologien dargelegt. Anhand eines Anforderungskataloges wird gezeigt, wie sich die Nachhaltigkeit eines Speichersystems bewerten lässt. Praktische Beispiele für nachhaltige Energiespeicher, z. B. Speicher für die Dunkelflaute, klimafreundliche Fahrzeuge und Solare Inselsysteme oder alternative Kraftstoffe für den Flugverkehr, veranschaulichen, wie sich eine ganzheitliche Energiewende realisieren lässt.

Nachhaltige Energiespeicher – ein kompakter Einstieg für Studierende und Ingenieure

Energiespeicher sind ein essentieller Bestandteil von Energiesystemen, um eine verlässliche Energieversorgung zu gewährleisten. Dies gilt insbesondere für erneuerbare Energien. Dabei sollen die Speichertechnologien selbst der Nachhaltigkeit nicht entgegenstehen. Dieses Buch richtet sich an Studierende der Elektro-, Umwelt- und Energietechnik sowie F&amp;E-Ingenieure, die vor der Herausforderung stehen, umweltverträgliche Energiespeicher zu entwickeln, die zugleich wirtschaftlich rentabel und gesellschaftlich akzeptiert sind.

Ausgehend von den physikalisch-chemischen Grundlagen der verschiedenen Speichertechnologien werden Funktionsweise, Anwendung und Komponenten folgender Speichersysteme erläutert:
- Mechanische Energiespeicher: Pumpspeicher, Druckluftspeicher
- Chemische Energiespeicher: Wasserstofftechnik, Methanisierung, biogene und synthetische Kraftstoffe
- Elektrochemische Energiespeicher: Batterien und Akkumulatoren, Brennstoffzellen und Redox-Flow-Systeme
- Thermische Energiespeicher: sensible Wärmespeicher, Latentwärmespeicher, Sorptionsspeicher

Neben den funktionalen Zusammenhängen werden die ökologischen, ökonomischen und sozialen Aspekte der Speichertechnologien dargelegt. Anhand eines Anforderungskataloges wird gezeigt, wie sich die Nachhaltigkeit eines Speichersystems bewerten lässt. Praktische Beispiele für nachhaltige Energiespeicher, z. B. Speicher für die Dunkelflaute, klimafreundliche Fahrzeuge und Solare Inselsysteme oder alternative Kraftstoffe für den Flugverkehr, veranschaulichen, wie sich eine ganzheitliche Energiewende realisieren lässt.

Technologien – Anwendungen – Bewertung

Nachhaltige Energiespeicher

Machine Learning Technologies on Energy Economics and Finance

Bibliografische Angaben

Schlagworte

Bibliografische Angaben

Schlagworte

Weitere Titel der Reihe: International Series in Operations Research & Management Science

Weitere Titel zum Thema