This book highlights recent developments in the field, presented at the Social Simulation 2015 conference in Groningen, The Netherlands. It covers advances both in applications and methods of social simulation. Societal issues addressed range across complexities in economic systems, opinion dynamics and civil violence, changing mobility patterns, different land-use, transition in the energy system, food production and consumption, ecosystem management and historical processes. Methodological developments cover how to use empirical data in validating models in general, formalization of behavioral theory in agent behavior, construction of artificial populations for experimentation, replication of models, and agent-based models that can be run in a web browser. Social simulation is a rapidly evolving field. Social scientists are increasingly interested in social simulation as a tool to tackle the complex non-linear dynamics of society. Furthermore, the software and hardware tools available for social simulation are becoming more and more powerful. This book is an important source for readers interested in the newest developments in the ways in which the simulation of social interaction contributes to our understanding and managing of complex social phenomena.

Energy is one of the worlds most challenging problems, and power systems are an important aspect of energy related issues. This handbook contains state-of-the-art contributions on power systems modeling and optimization. The book is separated into two volumes with six sections, which cover the most important areas of energy systems. The first volume covers the topics operations planning and expansion planning while the second volume focuses on transmission and distribution modeling, forecasting in energy, energy auctions and markets, as well as risk management. The contributions are authored by recognized specialists in their fields and consist in either state-of-the-art reviews or examinations of state-of-the-art developments. The articles are not purely theoretical, but instead also discuss specific applications in power systems.

The book offers a comprehensive survey of intuitionistic fuzzy logics. By reporting on both the author's research and others' findings, it provides readers with a complete overview of the field and highlights key issues and open problems, thus suggesting new research directions. Starting with an introduction to the basic elements of intuitionistic fuzzy propositional calculus, it then provides a guide to the use of intuitionistic fuzzy operators and quantifiers, and lastly presents state-of-the-art applications of intuitionistic fuzzy sets. The book is a valuable reference resource for graduate students and researchers alike.

This new edition focuses on three crucial areas of retail supply chain management: (1) empirical studies of retail supply chain practices, (2) assortment and inventory planning and (3) integrating price optimization into retail supply chain decisions. The book has been fully updated, expanding on the distinguishing features of the original, while offering three new chapters on recent topics which reflect areas of great interest and relevance to the academic and professional communities alike - inventory management in the presence of data inaccuracies, retail workforce management, and fast fashion retail strategies. The innovations, lessons for practice, and new technological solutions for managing retail supply chains are important not just in retailing, but offer crucial insights and strategies for the ultimate effective management of supply chains in other industries as well. The retail industry has emerged as a fascinating choice for researchers in the field of supply chain management. It presents a vast array of stimulating challenges that have long provided the context of much of the research in the area of operations research and inventory management. However, in recent years, advances in computing capabilities and information technologies, hyper-competition in the retail industry, emergence of multiple retail formats and distribution channels, an ever increasing trend towards a globally dispersed retail network, and a better understanding of the importance of collaboration in the extended supply chain have led to a surge in academic research on topics in retail supply chain management. Many supply chain innovations (e.g., vendor managed inventory) were first conceived and successfully validated in this industry, and have since been adopted in others. Conversely, many retailers have been quick to adopt cutting edge practices that first originated in other industries. Retail Supply Chain Management: Quantitative Models and Empirical Studies, 2nd Ed. is an attempt to summarize the state of the art in this research, as well as offer a perspective on what new applications may lie ahead.

This handbook serves as a complement to the Handbook on Data Envelopment Analysis (eds, W.W. Cooper, L.M. Seiford and J, Zhu, 2011, Springer) in an effort to extend the frontier of DEA research. It provides a comprehensive source for the state-of-the art DEA modeling on internal structures and network DEA. Chapter 1 provides a survey on two-stage network performance decomposition and modeling techniques. Chapter 2 discusses the pitfalls in network DEA modeling. Chapter 3 discusses efficiency decompositions in network DEA under three types of structures, namely series, parallel and dynamic. Chapter 4 studies the determination of the network DEA frontier. In chapter 5 additive efficiency decomposition in network DEA is discussed. An approach in scale efficiency measurement in two-stage networks is presented in chapter 6. Chapter 7 further discusses the scale efficiency decomposition in two stage networks. Chapter 8 offers a bargaining game approach to modeling two-stage networks. Chapter 9 studies shared resources and efficiency decomposition in two-stage networks. Chapter 10 introduces an approach to computing the technical efficiency scores for a dynamic production network and its sub-processes. Chapter 11 presents a slacks-based network DEA. Chapter 12 discusses a DEA modeling technique for a two-stage network process where the inputs of the second stage include both the outputs from the first stage and additional inputs to the second stage. Chapter 13 presents an efficiency measurement methodology for multi-stage production systems. Chapter 14 discusses network DEA models, both static and dynamic. The discussion also explores various useful objective functions that can be applied to the models to find the optimal allocation of resources for processes within the black box, that are normally invisible to DEA. Chapter 15 provides a comprehensive review of various type network DEA modeling techniques. Chapter 16 presents shared resources models for deriving aggregate measures of bank-branch performance, with accompanying component measures that make up that aggregate value. Chapter 17 examines a set of manufacturing plants operating under a single umbrella, with the objective being to use the component or function measures to decide what might be considered as each plant's core business. Chapter 18 considers problem settings where there may be clusters or groups of DMUs that form a hierarchy. The specific case of a set off electric power plants is examined in this context. Chapter 19 models bad outputs in two-stage network DEA. Chapter 20 presents an application of network DEA to performance measurement of Major League Baseball (MLB) teams. Chapter 21 presents an application of a two-stage network DEA model for examining the performance of 30 U.S. airline companies. Chapter 22 then presents two distinct network efficiency models that are applied to engineering systems.

This book examines agile approaches from a management perspective by focusing on matters of strategy, implementation, organization and people. It examines the turbulence of the marketplace and business environment in order to identify what role agile management has to play in coping with such change and uncertainty. Based on observations, personal experience and extensive research, it clearly identifies the fabric of the agile organization, helping managers to become agile leaders in an uncertain world. The book opens with a broad survey of agile strategies, comparing and contrasting some of the major methodologies selected on the basis of where they lie on a continuum of ceremony and formality, ranging from the minimalist technique-driven and software engineering focused XP, to the pragmatic product-project paradigm that is Scrum and its scaled counterpart SAFe (R), to the comparatively project-centric DSDM. Subsequently, the core of the book focuses on DSDM, owing to the method's comprehensive elaboration of program and project management practices. This work will chiefly be of interest to all those with decision-making authority within their organizations (e.g., senior managers, line managers, program, project and risk managers) and for whom topics such as strategy, finance, quality, governance and risk management constitute a daily aspect of their work. It will, however, also be of interest to those readers in advanced management or business administration courses (e.g., MBA, MSc), who wish to engage in the management of agile organizations and thus need to adapt their skills and knowledge accordingly.

1. 1 Motivation and Scope of Research Container terminals in seaports constitute interfaces between sea and land tra- port of goods in global transport chains. These logistics facilities face an increasing demandof service capacity, as is re ected by a tremendousgrowthin the worldwide container transshipments per year. For example, the top 20 terminals in the world showed an average relative increase of 14% with respect to the number of handled container units from 2006 to 2007, see Port of Hamburg Marketing (2008). In spite of this development, competition is high among container terminals within the same region. A terminal's customers, rst and foremost the vessel op- ators, expect a high level of service quality where reliability is one of the most importantdimensions, seeWiegmansetal. (2001). Regardingtheserviceofavessel, reliability means to realize all transshipment operations within its projected service time interval. The reliability of terminal operations impacts the reliability of v- sels in meeting their liner schedules. According to Notteboom (2006) unexpected waiting times of vessels before berthing and unexpected low transshipment prod- tivity at terminals are responsible for about 86% of liner schedule disturbances, see Fig. 1. 1. Currently, many terminal operators counteract this situation by extending their transshipment capacities. They build new terminals or enlarge existing ter- nals and purchase new or upgrade existing equipment. Ilmer (2005) provides an overview of current projects for building terminal capacity in northern Europe.

This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. In the third edition, much of the material has been reorganized, new examples have been added, and a new chapter has been added describing how modelers can improve the performance of their models. The authors have also modified their recommended method for importing Pyomo. A big change in this edition is the emphasis of concrete models, which provide fewer restrictions on the specification and use of Pyomo models. Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions.

Network Analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network is bringing together researchers, practitioners and other scientific communities from numerous fields such as Operations Research, Computer Science, Transportation, Energy, Social Sciences, and more. The remarkable diversity of fields that take advantage of Network Analysis makes the endeavor of gathering up-to-date material in a single compilation a useful, yet very difficult, task. The purpose of these proceedings is to overcome this difficulty by collecting the major results found by the participants of the "First International Conference in Network Analysis," held at The University of Florida, Gainesville, USA, from the 14th to the 16th of December 2011. The contributions of this conference not only come from different fields, but also cover a broad range of topics relevant to the theory and practice of network analysis, including the reliability of complex networks, software, theory, methodology and applications.

This book deals with transportation processes denoted as the Real-time Distribution of Perishable Goods (RDOPG). The book presents three contributions that are made to the field of transportation. First, a model considering the minimization of customer inconvenience is formulated. Second, a pro-active real-time control approach is proposed. Stochastic knowledge is generated from past request information by a new forecasting approach and is used in the pro-active approach to guide vehicles to request-likely areas before real requests arrive there. Various computational results are presented to show that in many cases the pro-active approach is able to achieve significantly improved results. Moreover, a measure for determining the structural quality of request data sets is also proposed. The third contribution of this book is a method that is presented for considering driver inconvenience aspects which arise from vehicle en-route diversion activities. Specifically, this method makes it possible to restrict the number of performed vehicle en-route diversion activities.

Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods presents the concepts and details of applications of MADM methods. A range of methods are covered including Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIsekriterijumsko KOmpromisno Rangiranje (VIKOR), Data Envelopment Analysis (DEA), Preference Ranking METHod for Enrichment Evaluations (PROMETHEE), ELimination Et Choix Traduisant la Realite (ELECTRE), COmplex PRoportional ASsessment (COPRAS), Grey Relational Analysis (GRA), UTility Additive (UTA), and Ordered Weighted Averaging (OWA). The existing MADM methods are improved upon and three novel multiple attribute decision making methods for solving the decision making problems of the manufacturing environment are proposed. The concept of integrated weights is introduced in the proposed subjective and objective integrated weights (SOIW) method and the weighted Euclidean distance based approach (WEDBA) to consider both the decision maker's subjective preferences as well as the distribution of the attributes data of the decision matrix. These methods, which use fuzzy logic to convert the qualitative attributes into the quantitative attributes, are supported by various real-world application examples. Also, computer codes for AHP, TOPSIS, DEA, PROMETHEE, ELECTRE, COPRAS, and SOIW methods are included. This comprehensive coverage makes Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods a key reference for the designers, manufacturing engineers, practitioners, managers, institutes involved in both design and manufacturing related projects. It is also an ideal study resource for applied research workers, academicians, and students in mechanical and industrial engineering.

This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.

With this book, distinguished and notable contributors wish to honor Professor Charles S. Tapiero s scientific achievements. Although it covers only a few of the directions Professor Tapiero has taken in his work, it presents important modern developments in theory and in diverse applications, as studied by his colleagues and followers, further advancing the topics Tapiero has been investigating. The book is divided into three parts featuring original contributions covering the following areas: general modeling and analysis; applications to marketing, economy and finance; and applications to operations and manufacturing.

Professor Tapiero is among the most active researchers in control theory; in the late sixties, he started to enthusiastically promote optimal control theory along with differential games, successfully applying it to diverse problems ranging from classical operations research models to finance, risk and insurance, marketing, transportation and operations management, conflict management and game theory, engineering, regional and urban sciences, environmental economics, and organizational behavior. Over the years, Professor Tapiero has produced over 300 papers and communications and 14 books, which have had a major impact on modern theoretical and applied research. Notable among his numerous pioneering scientific contributions are the use of graph theory in the behavioral sciences, the modeling of advertising as a random walk, the resolution of stochastic zero-sum differential games, the modeling of quality control as a stochastic competitive game, and the development of impulsive control methods in management. Charles Tapiero s creativity applies both in formulating original issues, modeling complex phenomena and solving complex mathematical problems."

Covering network designs, discrete convex analysis, facility location and clustering problems, matching games, and parameterized complexity, this book discusses theoretical aspects of combinatorial optimization and graph algorithms. Contributions are by renowned researchers who attended NII Shonan meetings on this essential topic. The collection contained here provides readers with the outcome of the authors' research and productive meetings on this dynamic area, ranging from computer science and mathematics to operations research. Networks are ubiquitous in today's world: the Web, online social networks, and search-and-query click logs can lead to a graph that consists of vertices and edges. Such networks are growing so fast that it is essential to design algorithms to work for these large networks. Graph algorithms comprise an area in computer science that works to design efficient algorithms for networks. Here one can work on theoretical or practical problems where implementation of an algorithm for large networks is needed. In two of the chapters, recent results in graph matching games and fixed parameter tractability are surveyed. Combinatorial optimization is an intersection of operations research and mathematics, especially discrete mathematics, which deals with new questions and new problems, attempting to find an optimum object from a finite set of objects. Most problems in combinatorial optimization are not tractable (i.e., NP-hard). Therefore it is necessary to design an approximation algorithm for them. To tackle these problems requires the development and combination of ideas and techniques from diverse mathematical areas including complexity theory, algorithm theory, and matroids as well as graph theory, combinatorics, convex and nonlinear optimization, and discrete and convex geometry. Overall, the book presents recent progress in facility location, network design, and discrete convex analysis.

Human and organizational factors have a substantial impact on the performance of planning and scheduling processes. Despite widespread and advanced decision support systems, human decision makers are still crucial to improve the operational performance in manufacturing industries. In this text, the state of the art in this area is discussed by experts from a wide variety of engineering and social science disciplines. Moreover, recent results from collaborative studies and a number of field cases are presented. The text is targeted at researchers and graduate students, but is also particularly useful for managers, consultants, and system developers to better understand how human performance can be advanced.

This book highlights some of the latest research advances and cutting-edge analyses of real-world case studies on Industrial Engineering and Operations Management from diverse international contexts, while also identifying business applications for the latest findings and innovations in operations management and the decision sciences. It gathers a selection of the best papers presented at the XXII International Conference on Industrial Engineering and Industrial Management, which was promoted by ADINGOR (Asociacion para el Desarrollo de la Ingenieria de Organizacion) and held at the Escola Politecnica Superior of the Universitat de Girona, Spain, on July 12th and 13th, 2018.

The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.

This book gathers selected peer-reviewed papers from the 14th World Congress on Engineering Asset Management (WCEAM), which was held in Singapore on 28-31 July 2019, as well as papers presented during the 1st WCEAMOnline event which focused on the ramifications of Covid-19 on infrastructure systems. This book covers a wide range of topics in engineering asset management, including: asset management services provisioning; servitization; decision-making; asset management systems; industrial Internet of things; and vulnerability and resilience of infrastructure systems. The breadth and depth of these state-of-the-art, comprehensive proceedings make them an excellent resource for asset management practitioners, researchers and academics, as well as undergraduate and postgraduate students.

Software Engineering Techniques Applied to Agricultural Systems presents cutting-edge software engineering techniques for designing and implementing better agricultural software systems based on the object-oriented paradigm and the Unified Modeling Language (UML). The focus is on the presentation of rigorous step-by-step approaches for modeling flexible agricultural and environmental systems, starting with a conceptual diagram representing elements of the system and their relationships. Furthermore, diagrams such as sequential and collaboration diagrams are used to explain the dynamic and static aspects of the software system. This second edition includes: a new chapter on Object Constraint Language (OCL), a new section dedicated to the Model-VIEW-Controller (MVC) design pattern, new chapters presenting details of two MDA-based tools - the Virtual Enterprise and Olivia Nova and a new chapter with exercises on conceptual modeling. It may be highly useful to undergraduate and graduate students as the first edition has proven to be a useful supplementary textbook for courses in mathematical programming in agriculture, ecology, information technology, agricultural operations research methods, agronomy and soil science and applied mathematical modeling. The book has broad appeal for anyone involved in software development projects in agriculture and to researchers in general who are interested in modeling complex systems. From the reviews of the first edition: "The book will be useful for those interested in gaining a quick understanding of current software development techniques and how they are applied in practice... this is a good introductory text on the application of OOAD, UML and design patters to the creation of agricultural systems. It is technically sound and well written." -Computing Reviews, September 2006

This volume chronicles the high impact research career of Harvey Greenberg (1940-2018), and in particular, it reviews historical contributions, presents current research projects, and suggests future pursuits. This volume addresses several of his most distinguished hallmarks, including model analysis, model generation, infeasibility diagnosis, sensitivity analysis, parametric programming, energy modeling, and computational biology. There is also an overview chapter on the emergence of computational OR, and in particular, how literature venues have changed the course of OR research. He developed Computer-Assisted Analysis in the 1970s and 80s, creating an artificially intelligent environment for analyzing mathematical programming models and their results. This earned him the first INFORMS Computing Society (ICS) Prize for "research excellence in the interfaces between operations research and computer science" in 1986, notably for his software system, ANALYZE. In 1993, he wrote the first book in the Springer OR/CS Series entitled A Computer-Assisted Analysis System for Mathematical Programming Models and Solutions: A User's Guide for ANALYZE. He applied OR methods to CS problems, ranging from using queuing theory for optimal list structure design to using integer programming for bioinformatic database search. He also applied CS to OR problems, ranging from super-sparse information structures to the use of compiler design in ANALYZE. This book can serve as a guide to new researchers, and will report the historical trajectory of OR as it solves current problems and forecasts future applications through the accomplishments of Harvey Greenberg.

Thecontinuousandincreasinginterestconcerningvectoroptimizationperc- tible in the research community, where contributions dealing with the theory of duality abound lately, constitutes the main motivation that led to writing this book. Decisive was also the research experience of the authors in this ?eld, materialized in a number of works published within the last decade. The need for a book on duality in vector optimization comes from the fact that despite the large amount of papers in journals and proceedings volumes, no book mainly concentrated on this topic was available so far in the scienti?c landscape. There is a considerable presence of books, not all recent releases, on vector optimization in the literature. We mention here the ones due to Chen,HuangandYang(cf. [49]),EhrgottandGandibleux(cf. [65]),Eichfelder (cf. [66]), Goh and Yang (cf. [77]), G.. opfert and Nehse (cf. [80]), G.. opfert, - ahi, Tammer and Z? alinescu (cf. [81]), Jahn (cf. [104]), Kaliszewski (cf. [108]), Luc (cf. [125]), Miettinen (cf. [130]), Mishra, Wang and Lai (cf. [131,132]) and Sawaragi, Nakayama and Tanino (cf. [163]), where vector duality is at most tangentially treated. We hope that from our e?orts will bene? t not only researchers interested in vector optimization, but also graduate and und- graduate students. The framework we consider is taken as general as possible, namely we work in (locally convex) topological vector spaces, going to the usual ?nite - mensional setting when this brings additional insights or relevant connections to the existing literature.

Over the last fifty-plus years, the increased complexity and speed of integrated circuits have radically changed our world. Today, semiconductor manufacturing is perhaps the most important segment of the global manufacturing sector. As the semiconductor industry has become more competitive, improving planning and control has become a key factor for business success. This book is devoted to production planning and control problems in semiconductor wafer fabrication facilities. It is the first book that takes a comprehensive look at the role of modeling, analysis, and related information systems for such manufacturing systems. The book provides an operations research- and computer science-based introduction into this important field of semiconductor manufacturing-related research.

Intelligent paradigms are increasingly finding their ways in the design and development of decision support systems. This book presents a sample of recent research results from key researchers. The contributions include: Introduction to intelligent systems in decision making - A new method of ranking intuitionistic fuzzy alternatives - Fuzzy rule base model identification by bacterial memetic algorithms - Discovering associations with uncertainty from large databases - Dempster-Shafer structures, monotonic set measures and decision making - Interpretable decision-making models - A general methodology for managerial decision making - Supporting decision making via verbalization of data analysis results using linguistic data summaries - Computational intelligence in medical decisions making.

This book is directed to the researchers, graduate students, professors, decision makers and to those who are interested to investigate intelligent paradigms in decision making.

This book surveys new algorithmic approaches and applications to natural and man-made disasters such as oil spills, hurricanes, earthquakes and wildfires. Based on the "Third International Conference on Dynamics of Disasters" held in Kalamata, Greece, July 2017, this Work includes contributions in evacuation logistics, disaster communications between first responders, disaster relief, and a case study on humanitarian logistics. Multi-disciplinary theories, tools, techniques and methodologies are linked with disasters from mitigation and preparedness to response and recovery. The interdisciplinary approach to problems in economics, optimization, government, management, business, humanities, engineering, medicine, mathematics, computer science, behavioral studies, emergency services, and environmental studies will engage readers from a wide variety of fields and backgrounds.

The book shows how simulation's long history and close ties to industry since the third industrial revolution have led to its growing importance in Industry 4.0. The book emphasises the role of simulation in the new industrial revolution, and its application as a key aspect of making Industry 4.0 a reality - and thus achieving the complete digitisation of manufacturing and business. It presents various perspectives on simulation and demonstrates its applications, from augmented or virtual reality to process engineering, and from quantum computing to intelligent management. Simulation for Industry 4.0 is a guide and milestone for the simulation community, as well as those readers working to achieve the goals of Industry 4.0. The connections between simulation and Industry 4.0 drawn here will be of interest not only to beginners, but also to practitioners and researchers as a point of departure in the subject, and as a guide for new lines of study.