Although studies on multiobjective mathematical programming under uncertainty have been accumulated and several books on multiobjective mathematical programming under uncertainty have been published (e.g., Stancu-Minasian (1984); Slowinski and Teghem (1990); Sakawa (1993); Lai and Hwang (1994); Sakawa (2000)), there seems to be no book which concerns both randomness of events related to environments and fuzziness of human judgments simultaneously in multiobjective decision making problems. In this book, the authors are concerned with introducing the latest advances in the field of multiobjective optimization under both fuzziness and randomness on the basis of the authors' continuing research works. Special stress is placed on interactive decision making aspects of fuzzy stochastic multiobjective programming for human-centered systems under uncertainty in most realistic situations when dealing with both fuzziness and randomness. Organization of each chapter is briefly summarized as follows:

Chapter 2 is devoted to mathematical preliminaries, which will be used throughout the remainder

of the book. Starting with basic notions and methods of multiobjective programming, interactive

fuzzy multiobjective programming as well as fuzzy multiobjective programming is outlined.

In Chapter 3, by considering the imprecision of decision maker's (DM's) judgment for stochastic

objective functions and/or constraints in multiobjective problems, fuzzy multiobjective stochastic

programming is developed.

In Chapter 4, through the consideration of not only the randomness of parameters involved in

objective functions and/or constraints but also the experts' ambiguous understanding of the realized values of the random parameters, multiobjective programming problems with fuzzy random variables are formulated.

In Chapter 5, for resolving conflict of decision making problems in hierarchical managerial or

public organizations where there exist two DMs who have different priorities in making decisions, two-level programming problems are discussed.

Finally, Chapter 6 outlines some future research directions.

Nowadays, decision problems are pervaded with incomplete knowledge, i.e., imprecision and/or uncertain information, both in the problem description and in the preferential information. In this volume leading scientists in the field address various theoretical and practical aspects related to the handling of this incompleteness. The problems discussed are taken from multi-objective linear programming, rationality considerations in preference modelling, non-probabilistic utility theory, data fusion, group decision making and multicriteria decision aid. The book is oriented towards researchers, graduate and postgraduate students in decision analysis, fuzzy sets and fuzzy logic, and operations research/management science.

This third edition, which has been fully updated and now includes improved and extended explanations, is suitable as a core textbook as well as a source book for industry practitioners. It covers traditional approaches for forecasting, lot sizing, determination of safety stocks and reorder points, KANBAN policies and Material Requirements Planning. It also includes recent advances in inventory theory, for example, new techniques for multi-echelon inventory systems and Roundy's 98 percent approximation. The book also considers methods for coordinated replenishments of different items, and various practical issues in connection with industrial implementation. Other topics covered in Inventory Control include: alternative forecasting techniques, material on different stochastic demand processes and how they can be fitted to empirical data, generalized treatment of single-echelon periodic review systems, capacity constrained lot sizing, short sections on lateral transshipments and on remanufacturing, coordination and contracts. As noted, the explanations have been improved throughout the book and the text also includes problems, with solutions in an appendix.

The book develops manufacturing concepts and applications beyond physical production and towards a wider manufacturing value chain incorporating external stakeholders that include suppliers of raw materials and parts, customers, collaborating manufacturing companies, manufacturing service providers, and environmental organisations. The focal point of the value chain remains as a manufacturing system and its operations whiles flows of parts/materials and information and services across the supply/value chain tiers are taken into account. The book emphasises on the two innovative paradigms of Reconfigurable Manufacturing Systems (RMS) and the 4th industrial revolution (Industry 4.0) along with their incorporated development. RMS, as a relatively new paradigm, has been introduced to meet the requirements of 'the factories of the future', which is aimed by Industry 4.0, though introducing greater responsiveness and customised flexibility into production systems, in which changes in product volumes and types occur regularly. Manufacturing responsiveness can be achieved by RMS through reconfiguring the production facilities according to changing demands of products and new market conditions. The book addresses challenges of mass-customisation and dynamic changes in the supply-chain environment by focusing on developing new techniques related to integrability, scalability and re-configurability at a system level and manufacturing readiness in terms of financial and technical feasibility of RMS. It demonstrate the expected impacts of an RMS design on operational performance and its supply/value chain in the current/future manufacturing environment facing dynamic changes in the internal/external circumstances. In order to establish a circular economy through the RMS value chain, an integrated data-based reconfiguration link is introduced to incorporate information sharing amongst the value chain stakeholders and facilitate grouping products into families with allocation of the product families to the corresponding system configurations with optimal product-process allocation. Decision support systems such as multi criteria decision making tools are developed and applied for the selection of product families and optimising product-process configuration. The proposed models are illustrated through real case studies in applicable manufacturing firms.

The issue of sustainability has become a vital discussion in many industries within the public and private sectors. In the business realm, incorporating such practices allows organizations to re-design their operations more effectively. Green Supply Chain Management for Sustainable Business Practice examines the challenges and benefits of implementing sustainability into the core functions of contemporary enterprises, focusing on how green approaches improve operations in an ecological way. Highlighting key concepts, emerging innovations, and future directions, this book is a pivotal reference source for professionals, managers, educators, and upper-level students.

This attractive textbook with its easy-to-follow presentation provides a down-to-earth introduction to operations research for students in a wide range of fields such as engineering, business analytics, mathematics and statistics, computer science, and econometrics. It is the result of many years of teaching and collective feedback from students.The book covers the basic models in both deterministic and stochastic operations research and is a springboard to more specialized texts, either practical or theoretical. The emphasis is on useful models and interpreting the solutions in the context of concrete applications.The text is divided into several parts. The first three chapters deal exclusively with deterministic models, including linear programming with sensitivity analysis, integer programming and heuristics, and network analysis. The next three chapters primarily cover basic stochastic models and techniques, including decision trees, dynamic programming, optimal stopping, production planning, and inventory control. The final five chapters contain more advanced material, such as discrete-time and continuous-time Markov chains, Markov decision processes, queueing models, and discrete-event simulation.Each chapter contains numerous exercises, and a large selection of exercises includes solutions.

This attractive textbook with its easy-to-follow presentation provides a down-to-earth introduction to operations research for students in a wide range of fields such as engineering, business analytics, mathematics and statistics, computer science, and econometrics. It is the result of many years of teaching and collective feedback from students.The book covers the basic models in both deterministic and stochastic operations research and is a springboard to more specialized texts, either practical or theoretical. The emphasis is on useful models and interpreting the solutions in the context of concrete applications.The text is divided into several parts. The first three chapters deal exclusively with deterministic models, including linear programming with sensitivity analysis, integer programming and heuristics, and network analysis. The next three chapters primarily cover basic stochastic models and techniques, including decision trees, dynamic programming, optimal stopping, production planning, and inventory control. The final five chapters contain more advanced material, such as discrete-time and continuous-time Markov chains, Markov decision processes, queueing models, and discrete-event simulation.Each chapter contains numerous exercises, and a large selection of exercises includes solutions.

National oil companies are big business with about 80 percent of the world's proven oil reserves, and they are crucial to the world's energy supplies. They are giants, some of the world's largest companies, measured by market capitalisation, cash flow and investment. Little is known about their modus operandi, how they make decisions about investment and production or about relations with their government-owners. However, it is known that they conduct business with a political mandate, often with multiple long-term objectives, broadly defined and hard to quantify. Unclear mandates give national oil companies leeway to pursue their own distinctive interests, apart from those of the government-owner. As investors, governments are less zealous than private investors. They generally observe multiple objectives, not only return on capital. Therefore, the senior management of national oil companies enjoy more discretionary power and consider longer time horizons than their counterparts in the private sector. The Oil Business and the State explains the practice of state ownership in a capital-intensive industry with high risks and high return, and how these companies act in a market with imperfect competition. This book looks to give readers more insight into the oil industry, into the background of oil exporting countries as well as the economic and political challenges confronting them, including problems of state ownership. The book discusses wider consequences of China replacing the United States as the world's leading oil importer. It will be of interest to researchers, academics and students in the fields of international business, management history, corporate governance, political economy and economic development of oil-rich countries.

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 focuses largely on constrained optimization. It begins with a substantial treatment of linear programming and proceeds to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. Along the way, dynamic programming and the linear complementarity problem are touched on as well. This book aims to be the first introduction to the topic. Specific examples and concrete algorithms precede more abstract topics. Nevertheless, topics covered are developed in some depth, a large number of numerical examples worked out in detail, and many recent results are included, most notably interior-point methods. The exercises at the end of each chapter both illustrate the theory, and, in some cases, extend it. Optimization is not merely an intellectual exercise: its purpose is to solve practical problems on a computer. Accordingly, the book comes with software that implements the major algorithms studied. At this point, software for the following four algorithms is available: The two-phase simplex method The primal-dual simplex method The path-following interior-point method The homogeneous self-dual methods.GBP/LISTGBP.

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.

The quadratic binary optimization problem (QUBO) is a versatile combinatorial optimization model with a variety of applications and rich theoretical properties. Application areas of the model include finance, cluster analysis, traffic management, machine scheduling, VLSI physical design, physics, quantum computing, engineering, and medicine. In addition, various mathematical optimization models can be reformulated as a QUBO, including the resource constrained assignment problem, set partitioning problem, maximum cut problem, quadratic assignment problem, the bipartite unconstrained binary optimization problem, among others. This book presents a systematic development of theory, algorithms, and applications of QUBO. It offers a comprehensive treatment of QUBO from various viewpoints, including a historical introduction along with an in-depth discussion of applications modelling, complexity and polynomially solvable special cases, exact and heuristic algorithms, analysis of approximation algorithms, metaheuristics, polyhedral structure, probabilistic analysis, persistencies, and related topics. Available software for solving QUBO is also introduced, including public domain, commercial, as well as quantum computing based codes.

First published in 2000. Routledge is an imprint of Taylor & Francis, an informa company.

The Fundamentals of Developing Operational Solutions for the Government guides professionals on how to use operations research to solve problems and capture opportunities for government customers. The governments of modern democratic nations manage large complex societal operations to offer national defense, social services, infrastructure sustainment, law enforcement, monetary control, and other benefits for their citizens. The United States government alone spends over $1 trillion per year on these discretionary activities. Within all the spending, deliveries, and oversight, some operational needs require solutions to improve processes, architectures, technologies, and human factors. Without such effective and comprehensive solutions, the most eloquent proposal for government work could end in defeat and the most well-funded government programs could yield operational disruptions and performance failures. There are many books on how to write winning proposals to the government, but this book places winning in the context of deeply understanding government operations and innovatively solving government problems. There are also some books on convincing the government to adopt new transformational processes, but this book seeks to first try to fix current government processes before demanding risky transformation. Finally, there are massive tomes dedicated to the theories and mathematical models of operations research, but this book is devoted to making operations research simple enough for professionals to apply throughout the course of developing proposals and delivering products and services. Presenting the methods and techniques for quickly developing solutions is thus the central focus.

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 book provides an in-depth analysis of investment problems pertaining to electric energy infrastructure, including both generation and transmission facilities. The analysis encompasses decision-making tools for expansion planning, reinforcement, and the selection and timing of investment options. In this regard, the book provides an up-to-date description of analytical tools to address challenging investment questions such as: How can we expand and/or reinforce our aging electricity transmission infrastructure? How can we expand the transmission network of a given region to integrate significant amounts of renewable generation? How can we expand generation facilities to achieve a low-carbon electricity production system? How can we expand the generation system while ensuring appropriate levels of flexibility to accommodate both demand-related and production-related uncertainties? How can we choose among alternative production facilities? What is the right time to invest in a given production or transmission facility? Written in a tutorial style and modular format, the book includes a wealth of illustrative examples to facilitate comprehension. It is intended for advanced undergraduate and graduate students in the fields of electric energy systems, operations research, management science, and economics. Practitioners in the electric energy sector will also benefit from the concepts and techniques presented here.

In an era of systemic crisis and of global critiques of the unsustainable perpetuation of capitalism, Pervasive Powers: The Politics of Corporate Authority critically questions the conditions for the maintenance and expansion of corporate power. The book explores empirical case studies in the realms of finance, urban policies, automobile safety, environmental risk, agriculture, and food in western democracies. It renews understanding of the power of big business, focusing on how the study of temporalities, of multi-sited influence and of sociotechnical tools is crucial to an analysis of the evolution of corporate authority. Drawing on different literatures, ranging from research on business associations and global governance to that on the social production of ignorance or on corporate crime, this book aims at contributing to existing works on the capacity of corporations to rule the world. Unlike approaches focused on economic elites and on the political activities of firms, it goes beyond analysis of the power of corporations to influence policy-making to depict their unprecedented capacity to transform and shape the social world. Operating in numerous social spaces and mobilizing a wide range of strategies, corporate organizations have acquired the pervasive power to act far beyond mere spaces of regulation and government. Based on contributions from historians, science and technology studies scholars, sociologists and political scientists, this book will be of great interest to researchers, academics and students who wish to understand how corporations exert a pervasive influence on public policies, and to NGOs and regulatory agencies.

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.

Through an exclusive focus on public policy advocacy, Dalton and Butler offer practical guidance for determining the fundamental issues that make up a controversy and what expectations public audiences will have for advocacy based on the issues and the burdens of advocates challenging or defending the status quo. Through examples that span a wide range of advocacy situations and subjects of contemporary importance, the authors build a framework for public policy advocacy that is organic to the communication discipline, recover and refresh foundational lessons about the uses of evidence, and provide critical questions that can be used to develop and communicate policy proposals that are sensible and appealing. Written in an accessible, respectful, and motivational style, the book is suitable for students of debate, professionals who function as advocates, and people who wish to voice their opinion.

The tactical organization of resources is a vital component to any industry in modern society. Effectively managing the flow of materials through various networks ensures that the requirements of customers are met. Sustainable Logistics and Strategic Transportation Planning is a pivotal reference source for the latest research on the management of logistics through the lens of sustainability, as well as for emerging procedures that are particularly critical to the transportation sector. Highlighting international perspectives, conceptual frameworks, and targeted investigations, this book is ideally designed for policy makers, professionals, researchers, and upper-level students interested in logistics and transport systems.

This book offers a comprehensive and systematic review of the latest research findings in the area of intuitionistic fuzzy calculus. After introducing the intuitionistic fuzzy numbers' operational laws and their geometrical and algebraic properties, the book defines the concept of intuitionistic fuzzy functions and presents the research on the derivative, differential, indefinite integral and definite integral of intuitionistic fuzzy functions. It also discusses some of the methods that have been successfully used to deal with continuous intuitionistic fuzzy information or data, which are different from the previous aggregation operators focusing on discrete information or data. Mainly intended for engineers and researchers in the fields of fuzzy mathematics, operations research, information science and management science, this book is also a valuable textbook for postgraduate and advanced undergraduate students alike.

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.

This book examines Multi-Criteria Decision Modelling (MCDM) methodologies and facilitates diverse ways for strategic decision-making in a variety of practical applications. This book also provides a pragmatic foundation for solving real-life problems in different scenarios of emerging global markets. Multi-Criteria Decision Modelling: Applicational Techniques and Case Studies depicts the use of sensitivity analysis and modelling and includes case studies to understand and illustrate challenging concepts. It also offers step-by-step comprehensive methodologies for the utilization of MCDM to a variety of situations. The book deliberates ways for companies to use these methods to their advantage in order to achieve sustainability. Furthermore, it also presents an overview of the major streams of thought and provides a holistic view of the latest research and development trends in modelling and optimization. FEATURES Offers a stepwise comprehensive methodology for the application of MCDM to a variety of situations Presents an overview of the major streams of thought present in the MCDM technique Provides a holistic view of the latest research and development trends in the emerging markets in terms of modelling and optimization using MCDM for different industrial sectors Illuminates a practical foundation in order to provide a guide to address the problems of emerging markets Enlightens the ways for companies to use these methods to their advantage to be able to achieve sustainability This book is a guide for those performing decision analysis for academic purposes as well as for researchers aspiring to expand their knowledge on MCDM problem solving.

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.

Presents an elucidative discussion about productivity and efficiency, illustrating its potentials of use and conceptual differencesCovers the concepts and techniques for analysis of productivity and efficiency, analyzing critical benefits and limitations Explains didactically and in detail how to use DEA for analysis of productivity and efficiency Provides an innovative method for using DEA Offers a free online computer tool to operationalize the concepts and method proposed in the book