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Public corporations and private businesses operate in an increasingly complex, uncertain, and interconnected world. When evaluating investment decisions, business managers can no longer base their decisions primarily on expected financial return. They now must now consider a host of performance value measures (i.e., criteria) pertaining to issues such as environmental and social governance, sustainability, and stakeholder satisfaction. In addition, corporate managers must ensure that their investment decisions are aligned with the company’s vision, mission, and values in order to maintain investor confidence and protect brand image. Lastly, to be truly successful, business managers must assess the risks associated with each performance measure and manage their impacts during project implementation. This book takes a pragmatic business and economics view towards evaluating competing investment alternatives and/or capital project strategies. It provides a practical step-by- step process using a structured decision analysis framework to evaluate, understand, quantify, and measure project invesment strategies in light of multiple stakeholder objectives and success criteria. This process assists in helping stakeholders (internal and external) achieve a shared understanding of project issues and to facilitate convergence towards a mutually acceptable solution. The approach considers available choices, identified uncertainties, constraints, necessary tradeoffs, and preferences so as to identify solutions that maximize overall benefits while minimizing overall costs and risk. A real world case study is presented in the early chapters and the process steps are demonstrated through application to this case study. Recent advances in technology allow for investment strategies to be evaluated against multiple criteria within one integrated platform. This book guides the reader in performing multi-criteria decision analysis, including the use of Monte Carlo simulation, within an MS Excel environment using native MS Excel and as well as add-in programs such Palisades Decision Tools suite. Example model structures, screen shots, formulas, and output results are provided throughout the book using an illustrative case study.

Decision Analysis, Financial Analysis, Operations Research/Management Science (ORMS), Business Analytics, Systems Modeling.

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This book offers essential information on the life and career of the recently deceased Giorgio P. Szegö, particularly his important contributions in various areas of mathematical programming and applications to financial markets. It highlights the developments in the fields of stability theory and dynamical systems brought about by his work in the early 1960s and 1970s, then moves on to address his valuable contributions to portfolio theory in the late 1970s and early 1980s, and, finally, examines his work in the field of risk management and the role of financial regulation in the late 1990s. The book explores Giorgio P. Szegö’s contributions in diverse research areas ranging from global optimization, theory of stability and dynamical systems to applications of financial mathematics to portfolio theory, risk measurement and financial regulation. It also covers his consulting work for such major international institutions as the IMF, World Bank and OECD.

Operations research. --- Management science. --- Risk management. --- Operations Research and Decision Theory. --- Operations Research, Management Science . --- IT Risk Management.

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After developing fuzzy set theory, many contributors focused their research on the extension of fuzzy sets and their computational methodologies, strengthening modern science and technology. In some real-life phenomena, the conventional methods and traditional fuzzy sets cannot be explained, whereas the extension of fuzzy sets and effective new computing methods can explain it adequately. This edited book presents a new view of fuzzy set-measurement methods entitled "Fuzzy Optimization, Decision Making and Operations Research: Theory and Applications", which deals with different perspectives and areas of research. All chapters are divided into three parts: fuzzy optimization, fuzzy decision-making, and fuzzy operation research. The goal of this book is to provide a relevant methodological framework covering the core fields of fuzzy decision-making method, fuzzy optimization method, fuzzy graphics method, fuzzy operations research, fuzzy optimization using graph theory, fuzzy support systems and its real and industrial applications. For many people, fuzzy words' industrial engineering and scientific meanings are still an advanced system for improving modern science and technology. Although fuzzy logic can be applied to many different areas, people do not know how different fuzzy approaches can be applied to various products currently on the market. It is written for professionals who wish to share their expertise, improve their findings, and provide relevant information in the fields of fuzzy methods and their application in decision-making, optimization theory, graph theory and operations research. This book is aimed at experts and practitioners in the fields of fuzzy optimization, fuzzy decision-making, and fuzzy operation research.

Operations research. --- Management science. --- Mathematical optimization. --- Functional analysis. --- Operator theory. --- Statistics. --- Operations Research, Management Science . --- Optimization. --- Functional Analysis. --- Operator Theory.

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This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization. MDP allows users to develop and formally support approximate and simple decision rules, and this book showcases state-of-the-art applications in which MDP was key to the solution approach. The book is divided into six parts. Part 1 is devoted to the state-of-the-art theoretical foundation of MDP, including approximate methods such as policy improvement, successive approximation and infinite state spaces as well as an instructive chapter on Approximate Dynamic Programming. It then continues with five parts of specific and non-exhaustive application areas. Part 2 covers MDP healthcare applications, which includes different screening procedures, appointment scheduling, ambulance scheduling and blood management. Part 3 explores MDP modeling within transportation. This ranges from public to private transportation, from airports and traffic lights to car parking or charging your electric car. Part 4 contains three chapters that illustrates the structure of approximate policies for production or manufacturing structures. In Part 5, communications is highlighted as an important application area for MDP. It includes Gittins indices, down-to-earth call centers and wireless sensor networks. Finally Part 6 is dedicated to financial modeling, offering an instructive review to account for financial portfolios and derivatives under proportional transactional costs. The MDP applications in this book illustrate a variety of both standard and non-standard aspects of MDP modeling and its practical use. This book should appeal to readers for practitioning, academic research and educational purposes, with a background in, among others, operations research, mathematics, computer science, and industrial engineering.

Operations research. --- Decision making. --- Management science. --- Probabilities. --- Operations Research/Decision Theory. --- Operations Research, Management Science. --- Probability Theory and Stochastic Processes.

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This proceedings volume gathers selected, blinded peer-reviewed contributions presented at the XXIX International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM), held in Lisbon, Portugal, from June 28th to 30th, 2023. This volume focuses especially on the applications of Industrial Engineering and Operations Management for research and practice. It includes relevant information for academics since most of the chapters focus on real-world case studies and systematic reviews. It also provides valuable insights for professionals in the industrial sector by presenting solutions to complex industrial challenges. The 2023 iteration of the IJCIEOM conference had the theme "Developing resilience in Industrial Engineering and Operations Management" and aimed to analyze the resilience of supply chains in the post-COVID-19 era. The works published in this volume focus on how Digital Transformation (DX) and Artificial Intelligence (AI) have made the manufacturing and service industry more resistant to VUCA elements (i.e., volatile, uncertain, complex, and ambiguous). Regarding DX and AI, the research specifically focused on supply chain management, project management, and Industry 4.0. Other studies explore how industrial engineering incorporated innovative and technological concepts into service and product operations. Overall, this volume provides a valuable resource for researchers and practitioners alike as it presents numerous relevant contributions in identifying new challenges and opportunities for industrial engineering and operations management. This conference was sponsored by renowned international industry engineering associations, particularly the American Society for Engineering Management (ASEM), the Institute of Industrial & Systems Engineers (IISE), and the Asociación para el Desarrollo de la Ingeniería de Organización (ADINGOR).

Operations research. --- Management science. --- Mathematical optimization. --- Production management. --- Operations Research, Management Science . --- Discrete Optimization. --- Operations Management. --- Industrial engineering --- Operations research