In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the "Advanced Analytics in Mining Engineering Book" as a practical road map and tools for unleashing the potential buried in your company's data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners - undergraduate and graduate IT and mining engineering students - with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain - in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins - in line with leading "digital" industries.

Covid-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting against the virus, enormously tap on the power of AI and its data analytics models for urgent decision supports at the greatest efforts, ever seen from human history. This book showcases a collection of important data analytics models that were used during the epidemic, and discusses and compares their efficacy and limitations. Readers who from both healthcare industries and academia can gain unique insights on how data analytics models were designed and applied on epidemic data. Taking Covid-19 as a case study, readers especially those who are working in similar fields, would be better prepared in case a new wave of virus epidemic may arise again in the near future.

This book covers a large spectrum of cutting-edge game theory applications in management science in which Professor Georges Zaccour has made significant contributions. The book consists of 21 chapters and highlights the latest treatments of game theory in various areas, including marketing, supply chains, energy and environmental management, and cyber defense. With this book, former Ph.D. students and successful research collaborators of Professor Zaccour wish to honor his many scientific achievements.

As service centred organisations become and focused on the customer, values are co-created with their customers through organisational capabilities. The central part of these capabilities is knowledge which is directly supported by information technology and the relationships between the service firms' knowledge, capabilities, IT and strategy is essential for superior value co-creation with customers. Knowledge Driven Service Innovation and Management: IT Strategies for Business Alignment and Value Creation provides a comprehensive collection of research and analysis on the principles of service, knowledge and organisational capabilities. This book aims to clarify IT strategy procedures and management practices and how they are used to shape a firm's knowledge organisations as well as facilitate service innovation and customer value co-creation.

Contains case studies from engineering and operations research

Includes commented literature for each chapter

Because it deals with sustainably supplying cities and reducing congestion and pollution related to goods transport in urban areas, city logistics is an important field in transportation sciences. These logistics systems need to be sustainable and reliable to ensure the continued flow of goods. Logistics and Transport Modeling in Urban Goods Movement is a pivotal reference source that provides vital research on the main approaches and techniques used in urban goods transport modelling while addressing planning and management issues. Highlighting topics such as urban logistics, vehicle routing, and greenhouse emissions, this book is ideally designed for civil/transport engineers, planners, transport economists, geographers, computer scientists, practitioners, professionals, researchers, and students seeking current research on urban goods modelling.

Foresight is an area within Futures Studies that focuses on critical thinking concerning long term developments, whether within the public sector or in industry and management, and is something of a sub-section of complexity and network science. This book examines developments in foresight methodologies and relates in its greater part to the work done in the context of the COSTA22 network of the EU on Foresight Methodologies. Foresight is a professional practice that supports significant decisions, and as such it needs to be more assured of its claims to knowledge (methodology). Foresight is practiced across many domains and is not the preserve of specialized futurists, or indeed of foresight specialists. However, the disciplines of foresight are not well articulated or disseminated across domains, leading to re-inventions and practice that does not make best use of experience in other domains.

The methodological development of foresight is an important task that aims at strengthening the pool of the tools available for application, thereby empowering the actors involved in foresight practice. Elaborating further on methodological issues, such as those presented in the present book, enables the actors involved in foresight to begin to critique current practice from this perspective and, thirdly, to begin to design foresight practice. The present trends towards methodological concerns indicates a move from given expert-predicted futures to one in which futures are nurtured through a dialogue among stakeholders. The book has four parts, each elaborating on a set of aspects of foresight methodologies. After an introductory section, Part II considers theorizing about foresight methodologies. Part III covers system content issues, and Part IV presents foresight tools and approaches."

This book aims to stimulate debate in the growing and highly controversial area of measuring scholarly work. The authors examine key aspects of this topic through the lens of the latest theoretical developments in service science and associated fields. It includes chapters explaining the theoretical developments and methodological aspects of measuring the quality of academic teaching and research, while other chapters provide a review and analysis of various types of scholarly work metrics and processes with examples from several countries, cultures, and educational systems. The current growing concern about higher education (HE) quality has prompted institutions to divide university teachers' work into different areas and to design methods aimed at measuring the productivity of these areas. It is widely accepted that the need to evaluate HE service quality is a relevant issue for any society. However, the authors argue that most of the current practices used in the pursuit of this objective are jeopardizing the future of the university as a place of knowledge generation, science evolution and professional education.

The book covers up-to-date theoretical and applied advances in grey systems theory from across the world and vividly presents the reader with the overall picture of this new theory and its frontier research. Many of the concepts, models and methods in the book are original by the authors, including simplified form of grey number, general grey number and the operations of grey numbers; the axiomatic system of buffer operators and a series of weakening and strengthening operators; a series of grey relational analysis models, including grey absolute, relative, synthetic, similarity, closeness, negative and three dimension degree, etc.; grey fixed weight clustering model, grey evaluation models based on center-point and end-point mixed possibility functions; original difference grey model (ODGM), even difference grey model (EDGM), discrete grey model (DGM), fractional grey models, self-memory grey models; multi-attribute intelligent grey target decision models, weight vector group with kernel and the weighted comprehensive clustering coefficient vector, and spectrum analysis of sequence operators, etc. This book will be appropriate as a reference and/or professional book for courses of grey system theory for graduate students or high-level undergraduate students, majoring in areas of science, technology, agriculture, medicine, astronomy, earth science, economics, and management. It can also be utilized by researchers and practitioners in research institutions, business entities, and government agencies.

This book describes an effective decision-making and planning architecture for enhancing the navigation capabilities of automated vehicles in the presence of non-detailed, open-source maps. The system involves dynamically obtaining road corridors from map information and utilizing a camera-based lane detection system to update and enhance the navigable space in order to address the issues of intrinsic uncertainty and low-fidelity. An efficient and human-like local planner then determines, within a probabilistic framework, a safe motion trajectory, ensuring the continuity of the path curvature and limiting longitudinal and lateral accelerations. LiDAR-based perception is then used to identify the driving scenario, and subsequently re-plan the trajectory, leading in some cases to adjustment of the high-level route to reach the given destination. The method has been validated through extensive theoretical and experimental analyses, which are reported here in detail.

This book introduces readers to a new approach to identifying stock market bubbles by using the illiquidity premium, a parameter derived by employing conic finance theory. Further, it shows how to develop the closed form formulas of the bid and ask prices of European options by using Black-Scholes and Kou models. By using the derived formulas and sliding windows technique, the book explains how to numerically calculate illiquidity premiums. The methods introduced here will enable readers interested in risk management, portfolio optimization and hedging in real-time to identify when asset prices are in a bubble state and when that bubble bursts. Moreover, the techniques discussed will allow them to accurately recognize periods of exuberance and panic, and to measure how different strategies work during these phases with respect to calmer periods of market behavior. A brief history of financial bubbles and an outlook on future developments serve to round out the coverage.

This book focuses on negotiation processes and how negotiation modeling frameworks and information technology can support these. A modeling framework for negotiation as a purposeful complex adaptive process is presented and computer-implemented in the first three chapters. Two game-theoretic contributions use non-cooperative games in extensive form and a computer-implemented graph model for conflict resolution, respectively. Two chapters use the negotiators' joint utility distribution to provide problem structure and computer support. A chapter on cognitive support uses restructurable modeling as a framework. One chapter matches information technologies with negotiation tasks. Another develops computer support based on preference programming. Two final chapters develop a stakeholder approach to support system evaluation, and a research framework for them, respectively. Negotiation Processes: Modeling Frameworks and Information Technology will be of interest to researchers and students in the areas of negotiation, group decision/negotiation support systems and management science, as well as to practising negotiators interested in this technology.

This book provides students and researchers with a resource that includes the current application of the multi-criteria decision theory in a variety of fields, including the environment, health care, engineering, and architecture. There are many critical parameters (criteria) that can directly or indirectly affect the consequences of various decisions. The application of the multi-criteria decision theory focusses mainly on the use of computational methods which include multiple criteria and orders of preference for the evaluation and the selection of the best option among many alternatives based on the desired outcome. The theory of multi-criteria decision making (MCDM) is an approach that can be extremely useful for students, managers, engineers of manufacturing companies, etc.

This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study. The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice. The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.

This book explores clustering operations in the context of social networks and consensus-reaching paths that take into account non-cooperative behaviors. This book focuses on the two key issues in large-scale group decision-making: clustering and consensus building. Clustering aims to reduce the dimension of a large group. Consensus reaching requires that the divergent individual opinions of the decision makers converge to the group opinion. This book emphasizes the similarity of opinions and social relationships as important measurement attributes of clustering, which makes it different from traditional clustering methods with single attribute to divide the original large group without requiring a combination of the above two attributes. The proposed consensus models focus on the treatment of non-cooperative behaviors in the consensus-reaching process and explores the influence of trust loss on the consensus-reaching process.The logic behind is as follows: firstly, a clustering algorithm is adopted to reduce the dimension of decision-makers, and then, based on the clusters' opinions obtained, a consensus-reaching process is carried out to obtain a decision result acceptable to the majority of decision-makers. Graduates and researchers in the fields of management science, computer science, information management, engineering technology, etc., who are interested in large-scale group decision-making and consensus building are potential audience of this book. It helps readers to have a deeper and more comprehensive understanding of clustering analysis and consensus building in large-scale group decision-making.

Using numerical examples to illustrate their concepts and results, this book examines recently developed fuzzy multi-criteria methods, such as Intuitionistic Fuzzy TOPSIS, Intuitionistic Fuzzy TOPSIS & DEA-AHP, Intuitionistic VIKOR, Pythagorean WASPAS, Pythagorean ENTROPI, Hesitant CBD, Hesitant MABAC, Triangular EDAS, Triangular PROMETHEE, q-Rung Orthopair COPRAS, and Fuzzy Type - 2 ELECTRE. Each chapter covers practical applications in addition to fresh developments and results. Given its structure and scope, the book can be used as a textbook in graduate courses on operations research and industrial engineering. It also offers a valuable resource for scientists working in a range of disciplines that require multi-criteria decision making.

The proliferation of new products has become a common phenomenon in today's business world. Most companies now offer hundreds, if not thousands, of stock keeping units (SKUs) in order to compete in the market place. Companies that expand their product and service varieties now face a new set of problems: accurate demand forecasts, controlling production and inventory costs, and providing high quality delivery performance. In addition, marketing managers will often advocate widening product lines for increasing revenue and market share, but increasing product lines can also decrease the efficiency of manufacturing processes and distribution systems. Hence, firms must weigh the benefits of increasing product variety against its cost and determine the optimal level of product variety to offer to their customers. Product Variety Management examines the interrelated problems between the marketing and production functions in industry, and through a series of research survey papers by leading scholars in economics, engineering, marketing, and operations research, the book addresses the following questions: Why do companies extend their product lines? Do consumers care about product variety? Will a brand with more variety enjoy higher market share? How should product variety be measured? How can a company exploit its product and process design to deliver a higher level of product variety quickly and cheaply? What should the level of product variety be and what should the price of each of the product variants be? What kind of challenges would a company face in offering a high level of product variety and how can these obstacles be overcome? The solutions to these questions are drawn frommultiple functions and a variety of disciplines. Product Variety Management is a state-of-the-art treatment of a multi-disciplinary approach to product variety.

1 Nabil R. Adam and Ali Dogramaci Measuring, analyzing, and improving productivity in a given organization is a complex process that involves the contributions of economists, industrial engineers, operations researchers, management scientists, and lawyers. The objective of this book is to provide the reader with a sample of original papers that relate to these productivity topics at the organizational level. In the book, the word organization refers to business firms and municipal organizations. The hook is divided into three parts: perspectives on productivity mea surement, a range of studies at the micro level, and some productivity issues in public organizations. Part I, which consists of three chapters, deals with productivity measurement. The first two chapters of this part cover a broad framework of measurement concepts and techniques; the last chapter, on the other hand, provides the reader with an example of productivity measurement for a specific industry (in this case, food retail ing). Thus, a spectrum of productivity measurement issues is covered in this part of the book."

The past decade has shown an increasing level of interest, research and application of quantitative models and computer based tools in the process industry. These models and tools constitute the basis of so-called Advanced Planning Systems which have gained considerable attention in practice. In particular, OR methodology has been applied to analyze and support the design of supply networks, the planning and scheduling of operations, and control issues arising in the production of food and beverages, chemicals, pharmaceutical, for instance. This book provides both new insights and successful solutions to problems of production planning and scheduling, logistics and supply chain management. It comprises reports on the state of the art, applications of quantitative methods, as well as case studies and success stories from industry. Its contributions are written by leading experts from academia and business. The book addresses practitioners working in industry as well as academic researchers in production, logistics, and supply chain management.   

This volume aims to provide a state-of-the-art and the latest advancements in the field of intelligent control and smart energy management. Techniques, combined with technological advances, have enabled the deployment of new operating systems in many engineering applications, especially in the domain of transport and renewable resources. The control and energy management of transportation and renewable resources are shifting towards autonomous reasoning, learning, planning and operating. As a result, these techniques, also referred to as autonomous control and energy management, will become practically ubiquitous soon. The discussions include methods, based on neural control (and others) as well as distributed and intelligent optimization. While the theoretical concepts are detailed and explained, the techniques presented are tailored to transport and renewable resources applications, such as smart grids and automated vehicles. The reader will grasp the most important theoretical concepts as well as to fathom the challenges and needs related to timely practical applications. Additional content includes research perspectives and future direction as well as insight into the devising of techniques that will meet tomorrow's scientific needs. This contributed volume is for researchers, graduate students, engineers and practitioners in the domains of control, energy, and transportation.

This proceedings volume convenes selected, peer-reviewed contributions presented at the POMS 2021 - International Conference on Production and Operations Management, which was virtually held in Lima, Peru, December 2-4, 2021. This book presents results in the field of Operations Management of key relevance to practitioners, instructors, and students. Topics focus on Operations Management, Logistics and Supply Chain Management, and Industrial and Production Engineering and Management, where mathematics and its applications play a role. In this work, readers will find a colorful collection of real-world case studies, accompanied by operations research-based managerial models. They touch on myriad topics, ranging from Artificial Intelligence and Data Analytics in Operations, Defense, Tourism, and other emerging issues in Operations Management to Healthcare Operations Management and Humanitarian Operations and Crisis Management. The POMS Lima 2021 International Conference has been organized by the Latin America & Caribbean Chapter of the Production and Operations Management Society, the most renowned professional and academic organization representing the interests of production and operations management professionals and academicians around the world. Since 2018, POMS International Conferences have been organized by POMS-LA, the first venue being in Rio de Janeiro, Brazil. Venue 2021 event was hosted by the Pontifical Catholic University of Peru and Pacific University, two Peruvian Latin-American leading academic institutions from Peru.

This book gathers selected peer-reviewed papers from the 16th World Congress on Engineering Asset Management (WCEAM), held in Seville from 5-7 October 2022. This book covers a wide range of topics in Engineering Asset Management, including: Asset management and decision support system Industry 4.0 tools and its impact on asset management Monitoring, diagnostics and prognostics for smart maintenance Asset life cycle management Asset management in the industrial sector Human dimensions and asset management performance Infrastructure Asset management Asset condition, risk, resilience, and vulnerability assessments Asset operations and maintenance strategies Reliability and resilience engineering Applications of international and local guidelines and standards The breadth and depth of this state-of-the-art, comprehensive proceedings make it an excellent resource for asset management practitioners, researchers and academics, as well as undergraduate and postgraduate students.

In a world with highly competitive markets and economic instability due to capitalization, industrial competition has increasingly intensified. In order for many industries to survive and succeed, they need to develop highly effective coordination between supply chain partners, dynamic collaborative and strategic alliance relationships, and efficient logistics and supply chain network designs. Consequently, in the past decade, there has been an explosion of interest among academic researchers and industrial practitioners in innovative supply chain and logistics models, algorithms, and coordination policies. Mathematically distinct from classical supply chain management, this emerging research area has been proven to be useful and applicable to a wide variety of industries. This book brings together recent advances in supply chain and logistics research and computational optimization that apply to a collaborative environment in the enterprise.

The book takes the inventory control perspective to tackle empty container repositioning logistics problems in regional transportation systems by explicitly considering the features such as demand imbalance over space, dynamic operations over time, uncertainty in demand and transport, and container leasing phenomenon. The book has the following unique features. First, it provides a discussion of broad empty equipment logistics including empty freight vehicle redistribution, empty passenger vehicle redistribution, empty bike repositioning, empty container chassis repositioning, and empty container repositioning (ECR) problems. The similarity and unique characteristics of ECR compared to other empty equipment repositioning problems are explained. Second, we adopt the stochastic dynamic programming approach to tackle the ECR problems, which offers an algorithmic strategy to characterize the optimal policy and captures the sequential decision-making phenomenon in anticipation of uncertainties over time and space. Third, we are able to establish closed-form solutions and structural properties of the optimal ECR policies in relatively simple transportation systems. Such properties can then be utilized to construct threshold-type ECR policies for more complicated transportation systems. In fact, the threshold-type ECR policies resemble the well-known (s, S) and (s, Q) policies in inventory control theory. These policies have the advantages of being decentralized, easy to understand, easy to operate, quick response to random events, and minimal on-line computation and communication. Fourth, several sophisticated optimization techniques such as approximate dynamic programming, simulation-based meta-heuristics, stochastic approximation, perturbation analysis, and ordinal optimization methods are introduced to solve the complex stochastic optimization problems. The book will be of interest to researchers and professionals in logistics, transport, supply chain, and operations research.

1 Ali Dogramaci and Nabil R. Adam 1.1. OVERVIEW With the decline of U.S. productivity growth, interest has surged to under stand the behavior of productivity measures through time, the conceptual foundations of productivity analysis, and the linkage between productivity performance and other major forces in the economy. The purpose of this volume is to present a brief overview of some of the concepts used in aggre gate and industry-level productivity analyses and the results of some of the recent research in this field. The book is divided into three parts. Part I covers some of the methodo logical approaches used in aggregate and industry-level productivity studies. Part II deals with the movement of labor productivity measures through time. The papers in this part of the book study productivity changes as uni variate time series and analyze some of the characteristics of the patterns displayed. The papers in Part III address the issues of measurement of capi tal, the relation of capital formation to productivity growth, and the rela tion of imported intermediate inputs to U.S. productivity performance."