A. Dogramaci and N.R. Adam Productivity of a firm is influenced both by economic forces which act at the macro level and impose themselves on the individual firm as well as internal factors that result from decisions and processes which take place within the boundaries of the firm. Efforts towards increasing the produc tivity level of firms need to be based on a sound understanding of how the above processes take place. Our objective in this volume is to present some of the recent research work in this field. The volume consists of three parts. In part I, two macro issues are addressed (taxation and inflation) and their relation to produc tivity is analyzed. The second part of the volume focuses on methods for productivity analysis within the firm. Finally, the third part of the book deals with two additional productivity analysis techniques and their applications to public utilities. The objective of the volume is not to present a unified point of view, but rather to cover a sample of different methodologies and perspectives through original, scholarly papers."

Each concept is discussed from the basics and supported by sufficient mathematical background and worked examples.

Suitable for individual or group learning, the book offers numerous end-of-chapter problems for study and review.

The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.

Applied Stochastic Models and Control for Finance and Insurance presents at an introductory level some essential stochastic models applied in economics, finance and insurance. Markov chains, random walks, stochastic differential equations and other stochastic processes are used throughout the book and systematically applied to economic and financial applications. In addition, a dynamic programming framework is used to deal with some basic optimization problems. The book begins by introducing problems of economics, finance and insurance which involve time, uncertainty and risk. A number of cases are treated in detail, spanning risk management, volatility, memory, the time structure of preferences, interest rates and yields, etc. The second and third chapters provide an introduction to stochastic models and their application. Stochastic differential equations and stochastic calculus are presented in an intuitive manner, and numerous applications and exercises are used to facilitate their understanding and their use in Chapter 3. A number of other processes which are increasingly used in finance and insurance are introduced in Chapter 4. In the fifth chapter, ARCH and GARCH models are presented and their application to modeling volatility is emphasized. An outline of decision-making procedures is presented in Chapter 6. Furthermore, we also introduce the essentials of stochastic dynamic programming and control, and provide first steps for the student who seeks to apply these techniques. Finally, in Chapter 7, numerical techniques and approximations to stochastic processes are examined. This book can be used in business, economics, financial engineering and decision sciences schools for second year Master's students, as well as in a number of courses widely given in departments of statistics, systems and decision sciences.

Data mining is the process of extracting hidden patterns from data, and it's commonly used in business, bioinformatics, counter-terrorism, and, increasingly, in professional sports. First popularized in Michael Lewis' best-selling Moneyball: The Art of Winning An Unfair Game, it is has become an intrinsic part of all professional sports the world over, from baseball to cricket to soccer. While an industry has developed based on statistical analysis services for any given sport, or even for betting behavior analysis on these sports, no research-level book has considered the subject in any detail until now. Sports Data Mining brings together in one place the state of the art as it concerns an international array of sports: baseball, football, basketball, soccer, greyhound racing are all covered, and the authors (including Hsinchun Chen, one of the most esteemed and well-known experts in data mining in the world) present the latest research, developments, software available, and applications for each sport. They even examine the hidden patterns in gaming and wagering, along with the most common systems for wager analysis.

This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies. Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a "big-data'" era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.

Computer-Integrated Manufacturing has gained recognition as a most effective tool in increasing manufacturing competitiveness. This book discusses the fundamental knowledge of Computer-Aided Process Planning, the key to integrated manufacturing.

The work provides a rigorous basis for the understanding of process planning and the development of effective and efficient Computer-Aided Process Planning systems. It presents a current overview on the latest issues and directions in this field. Topics covered include Group Technology, process planning algorithms, artificial intelligence, and assembly process planning. Most importantly, in order to provide a solid foundation for discussion and development, basic theories and principles for process planning are comprehensively and thoroughly studied in this book.

Written for those who wish to understand the theory of process planning, the book will also prove an indispensable reference source on the approaches, methodologies and tools which can be applied to day-to-day process planning operations.

Drawn from a conference honoring Gerald L. Thompson, the pioneer of operations research, this volume brings together some of the latest writings of major figures in the field. The volume is divided into four parts: the first part reviews the career and significance of Thompson, the second concentrates on linear and nonlinear optimization, the third looks at network and integer programming, and the fourth provides examples of applications-oriented research in manufacturing.

This volume will be an invaluable resource for all scholars and researchers involved in theory and methodology in operations research and management science.

1. 1. Motivation This book is based on the view-tx)int that both public and private decision making, in practice, can often be ilrproved upon by means of fonnal (nonnative) decision nodels and methods. To sane extent, the validity of this statement can be measured by the irrpressive number of su=esses of disciplines as operations research and management science. Hcwever, as witnessed by the many discussions in the professional journals in these fields, many rrodels and methods do not completely meet the requirements of decision making in prac- tice. Of all possible origins of these clear shortcomings, we main-* ly focus on only one: the fact that nost of these nodels and methods are unsuitable for decision situations in which multiple and possi- bly conflicting objectives playa role, because they are concentra- ted on the (optimal) fulfilment of only one objective. The need to account for multiple goals was observed relatively early. Hoffman [1955], while describing 'what seem to be the prin- cipal areas (in linear prograrrrning) where new ideas and new methods are needed' gives an exanple with conflicting goals. In this pro- blem, the assignrrent of relative weights is a great problem for the planning staff and is 'probably not the province of the mathemati- cian engaged in solving this problem'. These remarks were true pre- cursors of later develor:nents. Nevertheless, the need for methods dealing with multiple goals was not widely recognized until much later.

The fields of similarity and preference are still broadening due to the exploration of new fields of application. This is caused by the strong impact of vagueness, imprecision, uncertainty and dominance on human and agent information, communication, planning, decision, action, and control as well as by the technical progress of the information technology itself. The topics treated in this book are of interest to computer scientists, statisticians, operations researchers, experts in AI, cognitive psychologists and economists.

This book is a volume in honor of Zvi Drezner's 75th birthday. Professor Drezner is a leading scholar in location science. He received his BSc degree in Mathematics in 1965 and his PhD. in Computer Science ten years later, both from the Technion in Haifa, Israel. Since 1978 he has published in excess of 300 papers in refereed journals and books. He has received many honors, among them the University Outstanding Professor in 2005-6, the Outstanding Research Award (both from Cal State-Fullerton), the Location Analysis Lifetime Achievement Award from the Society for Location Analysis, and was named a Lifetime Fellow in INFORMS.Zvi has worked in a variety of fields, but most prominently in continuous location models. His main contributions include a 1982 paper on competitive location analysis, which was the first contribution to formally use the von Stackelberg "leader-follower" concept in the plane, contributions in 1989 (along with many others) on the Weber problem, and work with Oded Berman on the p-median under uncertainty in 2008. He has also enriched the literature by many contributions that devise genetic algorithms and tabu search techniques (both heuristic algorithms), as well as global optimization techniques, such as the "big-triangle-small-triangle" method, applied to location problems.The chapters of the book have been chosen to provide readers with a large variety of topics in the field of location science, which normally are available only in many different specialist journals. In addition to easily approachable surveys, the contributions, written by the top specialists in the field, present the latest results as well.

This volume presents state-of-the-art models, algorithms, and applications of quantitative methods in management and economics. The papers are clustered into four parts, focusing on optimization issues, applications of Operations Research in production and service management, applications of Operations Research in logistics, and interdisciplinary approaches.

This book offers a comprehensive introduction to fuzzy methods for solving flow tasks in both transportation and networks. It analyzes the problems of minimum cost and maximum flow finding with fuzzy nonzero lower flow bounds, and describes solutions to minimum cost flow finding in a network with fuzzy arc capacities and transmission costs. After a concise introduction to flow theory and tasks, the book analyzes two important problems. The first is related to determining the maximum volume for cargo transportation in the presence of uncertain network parameters, such as environmental changes, measurement errors and repair work on the roads. These parameters are represented here as fuzzy triangular, trapezoidal numbers and intervals. The second problem concerns static and dynamic flow finding in networks under fuzzy conditions, and an effective method that takes into account the network's transit parameters is presented here. All in all, the book provides readers with a practical reference guide to state-of-the art fuzzy methods for solving flow tasks and offers a valuable resource for all researchers and postgraduate students in the fields of network theory, fuzzy models and decision-making.

The book is an edited volume from leading research scholars in the field of Operations Research, focusing on future perspectives in OR. Each of the contributors offers their perspective looking forward to the further development of the field. The theme will provide pivotal interest in the book because of prominence of the contributors and Saul Gass' position as one of the founders of OR and his involvement in writing about the history of OR. The history of operations research is of considerable interest and this book takes a pivotal perspective of OR's history by examining current trends and the future of the field.

Over eleven years have passed since the last NATO sponsored meeting on Fishing which took the form of a Conference held in Trondheim in 1979. The proceedings contained in this book consist of papers presented in support of an Advanced Study Institute on Operations Research and Management in Fishing held at P6voa de Varzim, Portugal from March 25 to April 7 1990. It was originally intended to use the five themes, Production Functions and Management; Marine Fish Stocks; Fisheries Models; Fish Farming and Miscellaneous. There were no contributions on Fish Processing and the Fish Farming papers were not original. It was also decided to group the papers on Fisheries Models and Marine Fish Stocks together which means the proceedings has four headings: - Opening Session - Production Functions and Management - Marine Fish Stocks and Fisheries Models - Miscellaneous The contributions give a broad and complete overview of historical approaches and of recent trends on research in different sectors of fisheries. Criteria for quota distribution and schemes based on conclusions drawn from models and methods are presented. Surveillance methods are described in relation to species conservation and catch improvement. Different levels of regulatory enforcement are discussed and the implications of new technologies are introduced. Applications of Expert Systems to stock assessment and efficiency improvement in field sampling are presented. Models for fleet dispatch planning and fleet structure appraisal are introduced and procedures for operational capacity evaluation of fishery harbours are considered.

The purpose of the book is to put these new techniques at the disposal of researchers coming from different horizons, to assess the state of the art, to identify the capability of these new algorithms, to evidence the contribution of these methods to Economics and Management Sciences. It is a privileged place to expose the know-how and to discuss new developments and problems encountered in the researches.

The contributions in this book bring new confirmations of the interest of connectionist approaches for researchers in Economics and Management Sciences. The first part is dedicated to theoretical advances; the second part presents a wide range of applications. All papers contain interesting results on each subject, which would have been very difficult to show with classical techniques but which has been proven by using these connectionist non linear methods. They reflect the great diversity of connectionist approaches of which we know the reader will benefit for his(her) own research. If this study enlarges the range of analysis tools for researchers in Economics and Management we will have reached our goal of sharing our interest in these new and fascinating connectionist methods.

Evidence of lean thinking implementation is found in various areas such as services, healthcare, and different industries like the automotive industry, aerospace industry, textile industry, food industry, and oil and gas industry. Such evidence points to the universality of lean thinking and how its use in different contexts increases its importance as an approach to continuous improvement. Lean Thinking in Industry 4.0 and Services for Society presents an insight into lean thinking as a philosophy that can identify problems and wastes in various areas, analyze them, and identify activities that could improve processes. Covering key topics such as industrial systems, lean safety, and lean sustainability, this reference work is ideal for industry professionals, business owners, managers, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

Aimed at final year undergraduate students, this is the first volume to publish in a new series of text covering core subjects in operational research in an accessible student-friendly format. This volume presents simulation paired with inventory control. The Operational Research Series aims to provide a new generation of European-originated texts of practical relevance to todays student. To guarantee accessibility, the texts are concise and have a non-mathematical orientation. These texts will provide students with the grounding in operational research theory they need to become the innovators of tomorrow.

This book examines the different motivational policies used for inventory management. In many competitive markets, sellers use motivational policies to encourage the customers to buy more and these kinds of strategies are used as competitive tools. This book brings together all the motivational policies for lot sizing decisions and offers a useful guide for inventory control. Each chapter applies deterministic inventory models such as economic order quantity (EOQ) and economic production quantity (EPQ), but also stochastic models for the motivational policy covered. The book begins exploring quantity discounts such as all-unit and incremental discounts. It then looks at delayed payment or trade credit policies that are applied by many suppliers and/or wholesalers to increase their sales. The motivational policies covered in the following chapters are dedicated to advance payment/prepayment schemes and also special sales offered by retailers to increase sales levels or decrease the inventory level. Finally the book concludes with a review of announced price increases, which persuades customers to buy a product at the current price, rather than paying more for it in the future. Inventory Control Models with Motivational Policies should be useful for professionals working on supply chains, but also researchers in operations research and inventory management.

Web-Scale Discovery Services: Principles, Applications, Discovery Tools and Development Hypotheses summarizes and presents the state-of-the-art in WSDS. The title promotes a middle-way between finding the best tool for each particular need and the search for the most reliable systems. The title identifies basic theoretical problems and offers practical solutions for librarians. The volume offers a summary of ideas from around the world, giving a new perspective that is backed up by strong theory. Offering a vision for libraries, this book also allows archivists, museum specialists, computer scientists, commercial operators and interested users to deepen their culture and information literacy. The great number of information sources now available and the changing habits of web users has led to the development of Web Scale Discovery Services (WSDS). The goal of these systems and techniques is to make catalogues, databases, institutional repositories, Open Access archives and other databases searchable and discoverable through a single point of access. The diffusion of systems and connections between data disseminated by libraries and published by other institutions poses a challenge to understanding discovery in the modern library.

Facility location is concerned with the siting of one or more facilities in a way that optimizes certain objectives such as minimizing transportation costs, providing equitable service to customers, or minimizing the time taken to deliver emergency services. This handbook presents a wide-ranging survey of location analysis. Both researchers in the subject and practitioners concerned with the solution of real-world problems will find this an up-to-date and comprehensive volume which addresses all the major methods and applications in the field. Each chapter has been written by an expert on that particular topic, and the editor has taken care to ensure a uniformity of style and notation throughout. The book is organized into four parts: Methodology and analysis of facility location.- Various objectives in facility location.- Competitive facility location.- Routing and location.

The disciplines of computer science and operations research (OR) have been linked since their origins, each contributing to the dramatic advances of the other. This work explores the connections between these key technologies: how high-performance computing methods have led to advances in OR de ployment, and how OR has contributed to the design and development of ad vanced systems. The collected writings-from researchers and practitioners in Computer Science, Operations Research, Management Science, and Artificial Intelligence-were among those delivered at the Fifth INFORMS Computer Science Technical Section Conference in Dallas, Texas, January 8-10, 1996. The articles advance both theory and practice. Presented are new approaches to complex problems based on: metaheuristics (neural networks, genetic al gorithms, and Tabu Search), optimization and mathematical programming, stochastic methods, constraint programming, and logical analysis. These ad vanced methodologies are applied to new applications in such areas as: telecom munications network design, financial engineering, manufacturing, project man agement, and forecasting, airline and machine scheduling, vehicle routing, mod eling and decision support systems. Featured is a remarkable paper by keynote speaker Fred Glover, creator of the Tabu Search family of metaheuristics. In it he develops the principles of memory-based heuristic methods, contrasts them with the popular genetic algorithms and simulated annealing, provides a sweeping survey of application vignettes, and points to promising avenues for future research."

This is the Proceedings of the Eighth International Conference on Management Science and Engineering Management (ICMSEM) held from July 25 to 27, 2014 at Universidade Nova de Lisboa, Lisbon, Portugal and organized by International Society of Management Science and Engineering Management (ISMSEM), Sichuan University (Chengdu, China) and Universidade Nova de Lisboa (Lisbon, Portugal). The goals of the conference are to foster international research collaborations in Management Science and Engineering Management as well as to provide a forum to present current findings. A total number of 138 papers from 14 countries are selected for the proceedings by the conference scientific committee through rigorous referee review. The selected papers in the second volume are focused on Computing and Engineering Management covering areas of Computing Methodology, Project Management, Industrial Engineering and Information Technology.

This book discusses recent developments in the vast domain of optimization. Featuring papers presented at the 1st International Conference on Frontiers in Optimization: Theory and Applications (FOTA 2016), held at the Heritage Institute of Technology, Kolkata, on 24-26 December 2016, it opens new avenues of research in all topics related to optimization, such as linear and nonlinear optimization; combinatorial-, stochastic-, dynamic-, fuzzy-, and uncertain optimization; optimal control theory; as well as multi-objective, evolutionary and convex optimization and their applications in intelligent information and technology, systems science, knowledge management, information and communication, supply chain and inventory control, scheduling, networks, transportation and logistics and finance. The book is a valuable resource for researchers, scientists and engineers from both academia and industry.