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| lindo operations research: Operations Research Wayne L. Winston, 1987 |
| lindo operations research: Business Applications of Operations Research Bodhibrata Nag, 2013-12-09 Operations Research is a bouquet of mathematical techniques which have evolved over the last six decades, to improve the process of business decision making. Operations Research offers tools to optimize and find the best solutions to myriad decisions that managers have to take in their day to day operations or while carrying out strategic planning. Today, with the advent of operations research software, these tools can be applied by managers even without any knowledge of the mathematical techniques that underlie the solution procedures. The book starts with a brief introduction to various tools of operations research, such as linear programming, integer programming, multi-objective programming, queuing theory and network theory together with simple examples in each of the areas. Another introductory chapter on handling the operations research software, along with examples is also provided. The book intends to make the readers aware of the power and potential of operations research in addressing decision making in areas of operations, supply chain, financial and marketing management. The approach of this book is to demonstrate the solution to specific problems in these areas using operations research techniques and software. The reader is encouraged to use the accompanying software models to solve these problems, using detailed do-it-yourself instructions. The intended outcome for readers of this book will be gaining familiarity and an intuitive understanding of the various tools of operations research and their applications to various business situations. It is expected that this will give the reader the ability and confidence to devise models for their own business needs. |
| lindo operations research: Introduction to Operations Research Mr. Rohit Manglik, 2024-07-30 EduGorilla Publication is a trusted name in the education sector, committed to empowering learners with high-quality study materials and resources. Specializing in competitive exams and academic support, EduGorilla provides comprehensive and well-structured content tailored to meet the needs of students across various streams and levels. |
| lindo operations research: Operations Research Michael W. Carter, Camille C. Price, 2000-07-28 Students with diverse backgrounds will face a multitude of decisions in a variety of engineering, scientific, industrial, and financial settings. They will need to know how to identify problems that the methods of operations research (OR) can solve, how to structure the problems into standard mathematical models, and finally how to apply or develop computational tools to solve the problems. Perfect for any one-semester course in OR, Operations Research: A Practical Introduction answers all of these needs. In addition to providing a practical introduction and guide to using OR techniques, it includes a timely examination of innovative methods and practical issues related to the development and use of computer implementations. It provides a sound introduction to the mathematical models relevant to OR and illustrates the effective use of OR techniques with examples drawn from industrial, computing, engineering, and business applications Many students will take only one course in the techniques of Operations Research. Operations Research: A Practical Introduction offers them the greatest benefit from that course through a broad survey of the techniques and tools available for quantitative decision making. It will also encourage other students to pursue more advanced studies and provides you a concise, well-structured, vehicle for delivering the best possible overview of the discipline. |
| lindo operations research: Operation Research Dr. Akabarsaheb Babulal Nadaf, Dr. B.N. Naveen Kumar, Dr. Navneet Kumar Lamba, Dr. Amit Chauhan, 2025-02-28 Operations Research that mathematical and analytical techniques for decision-making and problem-solving in complex systems. Covering topics such as linear programming, queuing theory, game theory, inventory management, and simulation, the provides a structured approach to optimizing resources, minimizing costs, and improving efficiency. It integrates theoretical foundations with real-world applications in business, engineering, and logistics. Designed for students, researchers, and professionals, this offers in-depth explanations, case studies, and problem-solving strategies, making it an essential guide for mastering the principles and methodologies of operations research. |
| lindo operations research: Applications of Optimization with Xpress-MP Christelle Guéret, Christian Prins, Marc Sevaux, 2002 |
| lindo operations research: Linear and Integer Optimization Gerard Sierksma, Yori Zwols, 2015-05-01 Presenting a strong and clear relationship between theory and practice, Linear and Integer Optimization: Theory and Practice is divided into two main parts. The first covers the theory of linear and integer optimization, including both basic and advanced topics. Dantzig's simplex algorithm, duality, sensitivity analysis, integer optimization models |
| lindo operations research: Modeling, Analysis and Optimization of Process and Energy Systems F. Carl Knopf, 2011-12-14 Energy costs impact the profitability of virtually all industrial processes. Stressing how plants use power, and how that power is actually generated, this book provides a clear and simple way to understand the energy usage in various processes, as well as methods for optimizing these processes using practical hands-on simulations and a unique approach that details solved problems utilizing actual plant data. Invaluable information offers a complete energy-saving approach essential for both the chemical and mechanical engineering curricula, as well as for practicing engineers. |
| lindo operations research: Introduction to Mathematical Programming Wayne L. Winston, 1995 CD-ROM contains LINDO 6.1, LINGO 7.0, NeuralWorks Predict, Premium Solver for Education and examples files. |
| lindo operations research: Linear Programming G. V. Shenoy, 2007 Due To The Availability Of Computer Packages, The Use Of Linear Programming Technique By The Managers Has Become Universal. This Text Has Been Written Primarily For Management Students And Executives Who Have No Previous Background Of Linear Programming. The Text Is Oriented Towards Introducing Important Ideas In Linear Programming Technique At A Fundamental Level And Help The Students In Understanding Its Applications To A Wide Variety Of Managerial Problems. In Order To Strengthen The Understanding, Each Concept Has Been Illustrated With Examples. The Book Has Been Written In A Simple And Lucid Language And Has Avoided Mathematical Derivations So As To Make It Accessible To Every One.The Text Can Be Used In Its Entirely In A Fifteen Session Course At Programmes In Management, Commerce, Economics, Engineering Or Accountancy. The Text Can Be Used In One/Two Week Management/Executive Development Programmes To Be Supplemented With Some Cases. Practicing Managers And Executives, Computer Professionals, Industrial Engineers, Chartered And Cost Accountants And Economic Planners Would Also Find This Text Useful. |
| lindo operations research: Operations Research Wayne L. Winston, 1994 This book is intended to be used as an advanced beginning or an intermediate text in operations research, management science, or mathematical programming. |
| lindo operations research: Introduction to Operations Research Frederick S. Hillier, Gerald J. Lieberman, 2010 For over four decades, Introduction to Operations Research by Frederick Hillier has been the classic text on operations research. While building on the classic strengths of the text, the author continues to find new ways to make the text current and relevant to students. One way is by incorporating a wealth of state-of-the-art, user-friendly software and more coverage of business applications than ever before. The hallmark features of this edition include clear and comprehensive coverage of fundamentals, an extensive set of interesting problems and cases, and state-of-the-practice operations research software used in conjunction with examples from the text. The ninth edition introduces a new partnership with the Institute for Operations Research and Management (INFORMS). These two pillars of the OR world have come together to showcase some of the award-winning applications of operations research and integrate them with this text. |
| lindo operations research: Operations Research and Management Science Handbook A. Ravi Ravindran, 2016-04-19 Operations Research (OR) began as an interdisciplinary activity to solve complex military problems during World War II. Utilizing principles from mathematics, engineering, business, computer science, economics, and statistics, OR has developed into a full fledged academic discipline with practical application in business, industry, government and m |
| lindo operations research: Mixed Integer Nonlinear Programming Jon Lee, Sven Leyffer, 2011-12-02 Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances. |
| lindo operations research: Applied Integer Programming Der-San Chen, Robert G. Batson, Yu Dang, 2011-09-20 An accessible treatment of the modeling and solution of integer programming problems, featuring modern applications and software In order to fully comprehend the algorithms associated with integer programming, it is important to understand not only how algorithms work, but also why they work. Applied Integer Programming features a unique emphasis on this point, focusing on problem modeling and solution using commercial software. Taking an application-oriented approach, this book addresses the art and science of mathematical modeling related to the mixed integer programming (MIP) framework and discusses the algorithms and associated practices that enable those models to be solved most efficiently. The book begins with coverage of successful applications, systematic modeling procedures, typical model types, transformation of non-MIP models, combinatorial optimization problem models, and automatic preprocessing to obtain a better formulation. Subsequent chapters present algebraic and geometric basic concepts of linear programming theory and network flows needed for understanding integer programming. Finally, the book concludes with classical and modern solution approaches as well as the key components for building an integrated software system capable of solving large-scale integer programming and combinatorial optimization problems. Throughout the book, the authors demonstrate essential concepts through numerous examples and figures. Each new concept or algorithm is accompanied by a numerical example, and, where applicable, graphics are used to draw together diverse problems or approaches into a unified whole. In addition, features of solution approaches found in today's commercial software are identified throughout the book. Thoroughly classroom-tested, Applied Integer Programming is an excellent book for integer programming courses at the upper-undergraduate and graduate levels. It also serves as a well-organized reference for professionals, software developers, and analysts who work in the fields of applied mathematics, computer science, operations research, management science, and engineering and use integer-programming techniques to model and solve real-world optimization problems. |
| lindo operations research: Lean and Green Supply Chain Management Turan Paksoy, Gerhard-Wilhelm Weber, Sandra Huber, 2018-11-11 This book presents the latest developments in optimization and optimal control models; exact, approximate and hybrid methods; and their applications in lean and green supply chains. It examines supply chain network design and modeling, closed loop supply chains, and lean, green, resilient and agile or responsive networks, and also discusses corporate social responsibility and occupational health and safety. It particularly focuses on supply chain management under uncertainty – employing stochastic or nonlinear modeling, simulation based studies and optimization – multi-criteria decision-making and applications of fuzzy set theory, and covers various aspects of supply chain management such as risk management, supplier selection or the design of automated warehouses. Lastly, using experimental applications and practical case studies, it shows the impact of lean and green applications on vehicle/fleet management and operations management. |
| lindo operations research: Applied Integer Programming Der-San Chen, Robert G. Batson, Yu Dang, 2010-01-12 An accessible treatment of the modeling and solution of integer programming problems, featuring modern applications and software In order to fully comprehend the algorithms associated with integer programming, it is important to understand not only how algorithms work, but also why they work. Applied Integer Programming features a unique emphasis on this point, focusing on problem modeling and solution using commercial software. Taking an application-oriented approach, this book addresses the art and science of mathematical modeling related to the mixed integer programming (MIP) framework and discusses the algorithms and associated practices that enable those models to be solved most efficiently. The book begins with coverage of successful applications, systematic modeling procedures, typical model types, transformation of non-MIP models, combinatorial optimization problem models, and automatic preprocessing to obtain a better formulation. Subsequent chapters present algebraic and geometric basic concepts of linear programming theory and network flows needed for understanding integer programming. Finally, the book concludes with classical and modern solution approaches as well as the key components for building an integrated software system capable of solving large-scale integer programming and combinatorial optimization problems. Throughout the book, the authors demonstrate essential concepts through numerous examples and figures. Each new concept or algorithm is accompanied by a numerical example, and, where applicable, graphics are used to draw together diverse problems or approaches into a unified whole. In addition, features of solution approaches found in today's commercial software are identified throughout the book. Thoroughly classroom-tested, Applied Integer Programming is an excellent book for integer programming courses at the upper-undergraduate and graduate levels. It also serves as a well-organized reference for professionals, software developers, and analysts who work in the fields of applied mathematics, computer science, operations research, management science, and engineering and use integer-programming techniques to model and solve real-world optimization problems. |
| lindo operations research: Optimization and Decision Support Systems for Supply Chains Ana Paula Barbosa Póvoa, Albert Corominas, João Luís de Miranda, 2016-09-13 This contributed volume presents a collection of materials on supply chain management including industry-based case studies addressing petrochemical, pharmaceutical, manufacturing and reverse logistics topics. Moreover, the book covers sustainability issues, as well as optimization approaches. The target audience comprises academics, industry managers, and practitioners in the field of supply chain management, being the book also beneficial for graduate students |
| lindo operations research: Introduction to Mathematical Programming Wayne L. Winston, Munirpallam Venkataramanan, Winston, 2003 The student solutions manual provides worked out solutions to 1/3 of the problems in the text. |
| lindo operations research: Optimization Modeling with LINDO Linus E. Schrage, 1997 This successful book and software package--used by thousands of students and companies worldwide--shows readers how to apply optimization modeling to real business and industrial problems using LINDO for Windows. |
| lindo operations research: Chemical Production Scheduling Christos Maravelias, 2021-05-06 Understand common scheduling as well as other advanced operational problems with this valuable reference from a recognized leader in the field. Beginning with basic principles and an overview of linear and mixed-integer programming, this unified treatment introduces the fundamental ideas underpinning most modeling approaches, and will allow you to easily develop your own models. With more than 150 figures, the basic concepts and ideas behind the development of different approaches are clearly illustrated. Addresses a wide range of problems arising in diverse industrial sectors, from oil and gas to fine chemicals, and from commodity chemicals to food manufacturing. A perfect resource for engineering and computer science students, researchers working in the area, and industrial practitioners. |
| lindo operations research: Introduction to Operations Research Frederick S. Hillier, Gerald J. Lieberman, 1990 |
| lindo operations research: Modeling Decisions for Artificial Intelligence Vincenc Torra, Yasuo Narukawa, Aïda Valls, Josep Domingo-Ferrer, 2006-03-20 This book constitutes the refereed proceedings of the Third International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2006, held in Tarragona, Spain, in April 2006. The 31 revised full papers presented together with 4 invited lectures were thoroughly reviewed and selected from 97 submissions. The papers are devoted to theory and tools for modeling decisions, as well as applications that encompass decision making processes and information fusion techniques. |
| lindo operations research: Applied Decision Support with Soft Computing Xinghuo Yu, 2012-12-06 Soft computing has provided sophisticated methodologies for the development of intelligent decision support systems. Fast advances in soft computing technologies, such as fuzzy logic and systems, artificial neural networks and evolutionary computation, have made available powerful problem representation and modelling paradigms, and learning and optimisation mechanisms for addressing modern decision making issues. This book provides a comprehensive coverage of up-to-date conceptual frameworks in broadly perceived decision support systems and successful applications. Different from other existing books, this volume predominately focuses on applied decision support with soft computing. Areas covered include planning, management finance and administration in both the private and public sectors. |
| lindo operations research: Operations Research Hamdy A. Taha, 1976 |
| lindo operations research: Agent-Based Hybrid Intelligent Systems Zili Zhang, Chengqi Zhang, 2004-01-30 Solving complex problems in real-world contexts, such as financial investment planning or mining large data collections, involves many different sub-tasks, each of which requires different techniques. To deal with such problems, a great diversity of intelligent techniques are available, including traditional techniques like expert systems approaches and soft computing techniques like fuzzy logic, neural networks, or genetic algorithms. These techniques are complementary approaches to intelligent information processing rather than competing ones, and thus better results in problem solving are achieved when these techniques are combined in hybrid intelligent systems. Multi-Agent Systems are ideally suited to model the manifold interactions among the many different components of hybrid intelligent systems. This book introduces agent-based hybrid intelligent systems and presents a framework and methodology allowing for the development of such systems for real-world applications. The authors focus on applications in financial investment planning and data mining. |
| lindo operations research: Large Scale Optimization in Supply Chains and Smart Manufacturing Jesús M. Velásquez-Bermúdez, Marzieh Khakifirooz, Mahdi Fathi, 2019-09-06 In this book, theory of large scale optimization is introduced with case studies of real-world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders’ decomposition, logic-based Benders’ decomposition, Lagrangian relaxation, Dantzig –Wolfe decomposition, multi-tree decomposition, Van Roy’ cross decomposition and parallel decomposition for mathematical programs such as mixed integer nonlinear programming and stochastic programming. Case studies of large scale optimization in supply chain management, smart manufacturing, and Industry 4.0 are investigated with efficient implementation for real-time solutions. The features of case studies cover a wide range of fields including the Internet of things, advanced transportation systems, energy management, supply chain networks, service systems, operations management, risk management, and financial and sales management. Instructors, graduate students, researchers, and practitioners, would benefit from this book finding the applicability of large scale optimization in asynchronous parallel optimization, real-time distributed network, and optimizing the knowledge-based expert system for convex and non-convex problems. |
| lindo operations research: Linear Programming for Beginners Doris Lloyd Grosh, 2010 This book fills a gap in the linear programming literature, by explaining the steps that are illustrated but not always fully explained in every elementary operations book - the steps that lead from the elementary and intuitive graphical method of solution to the more advanced simplex tableau method. Most of the world, even those technically trained, can get along very well by seeing a few illustrations of simple linear programming problems solved graphically, followed by instruction in the use of computer software for solving real-world problems. But there needs to be a coterie of initiates who understand the process well enough to explain it to others, to know what the pitfalls, ramifications and special cases are, and to provide further developments. I have used an informal narrative style with a number of worked out examples and detailed explanations, to put the topic within reach. |
| lindo operations research: The Planning and Scheduling of Production Systems Abdelhakim Artiba, Salah E. Elmaghraby, 2012-12-06 If one accepts the premise that there is no wealth without production, whether at the individual or national level, one is immediately led to the conclusion that the study of productive systems lies at the forefront of subjects that should be intensively, as well as rationally and extensively, studied to achieve the desired 'sustainable growth' of society, where the latter is defined as growth in the quality of life that does not waste the available resources in the long run. Since the end of World War II there has been a remarkable evolution in thinking about production, abetted to a large measure by the nascent field of informatics: the computer technology and the edifices that have been built around it, such as information gathering and dissemination worldwide through communication networks, software products, peripheral interfaces, etc. Additionally, the very thought processes that guide and motivate studies in production have undergone fundamental changes which verge on being revolutionary, thanks to developments in operations research and cybernetics. |
| lindo operations research: Decision Modelling and Information Systems Nikitas-Spiros Koutsoukis, Gautam Mitra, 2012-12-06 In Decision Modelling And Information Systems: The Information Value Chain the authors explain the interrelationships between the decision support, decision modelling, and information systems. The first two parts of the book focus on the interdisciplinary decision support framework, in which mathematical programming (optimization) is taken as the inference engine. The role of business analytics and its relationship with recent developments in organisational theory, decision modelling, information systems and information technology are considered in depth. Part three of the book includes a carefully chosen selection of invited contributions from internationally-known researchers. These contributions are thought-provoking and cover key decision modelling and information systems issues. The final part of the book covers contemporary developments in the related area of business intelligence considered within an organizational context. The topics cover computing delivered across the web, management decision-making, and socio-economic challenges that lie ahead. It is now well accepted that globalisation and the impact of digital economy are profound; and the role of e-business and the delivery of decision models (business analytics) across the net lead to a challenging business environment. In this dynamic setting, decision support is one of the few interdisciplinary frameworks that can be rapidly adopted and deployed to so that businesses can survive and prosper by meeting these new challenges. |
| lindo operations research: Frontiers in Global Optimization Christodoulos A. Floudas, Panos M. Pardalos, 2013-12-01 Global Optimization has emerged as one of the most exciting new areas of mathematical programming. Global optimization has received a wide attraction from many fields in the past few years, due to the success of new algorithms for addressing previously intractable problems from diverse areas such as computational chemistry and biology, biomedicine, structural optimization, computer sciences, operations research, economics, and engineering design and control. This book contains refereed invited papers submitted at the 4th international confer ence on Frontiers in Global Optimization held at Santorini, Greece during June 8-12, 2003. Santorini is one of the few sites of Greece, with wild beauty created by the explosion of a volcano which is in the middle of the gulf of the island. The mystic landscape with its numerous mult-extrema, was an inspiring location particularly for researchers working on global optimization. The three previous conferences on Recent Advances in Global Opti mization, State-of-the-Art in Global Optimization, and Optimization in Computational Chemistry and Molecular Biology: Local and Global approaches took place at Princeton University in 1991, 1995, and 1999, respectively. The papers in this volume focus on de terministic methods for global optimization, stochastic methods for global optimization, distributed computing methods in global optimization, and applications of global optimiza tion in several branches of applied science and engineering, computer science, computational chemistry, structural biology, and bio-informatics. |
| lindo operations research: Aimms Optimization Modeling Johannes Bisschop, 2006 The AIMMS Optimization Modeling book provides not only an introduction to modeling but also a suite of worked examples. It is aimed at users who are new to modeling and those who have limited modeling experience. Both the basic concepts of optimization modeling and more advanced modeling techniques are discussed. The Optimization Modeling book is AIMMS version independent. |
| lindo operations research: Wireless Network Design Jeff Kennington, Eli Olinick, Dinesh Rajan, 2010-11-10 This book surveys state-of-the-art optimization modeling for design, analysis, and management of wireless networks, such as cellular and wireless local area networks (LANs), and the services they deliver. The past two decades have seen a tremendous growth in the deployment and use of wireless networks. The current-generation wireless systems can provide mobile users with high-speed data services at rates substantially higher than those of the previous generation. As a result, the demand for mobile information services with high reliability, fast response times, and ubiquitous connectivity continues to increase rapidly. The optimization of system performance has become critically important both in terms of practical utility and commercial viability, and presents a rich area for research. In the editors' previous work on traditional wired networks, we have observed that designing low cost, survivable telecommunication networks involves extremely complicated processes. Commercial products available to help with this task typically have been based on simulation and/or proprietary heuristics. As demonstrated in this book, however, mathematical programming deserves a prominent place in the designer's toolkit. Convenient modeling languages and powerful optimization solvers have greatly facilitated the implementation of mathematical programming theory into the practice of commercial network design. These points are equally relevant and applicable in today’s world of wireless network technology and design. But there are new issues as well: many wireless network design decisions, such as routing and facility/element location, must be dealt with in innovative ways that are unique and distinct from wired (fiber optic) networks. The book specifically treats the recent research and the use of modeling languages and network optimization techniques that are playing particularly important and distinctive roles in the wireless domain. |
| lindo operations research: Optimization Software Class Libraries Stefan Voß, David L. Woodruff, 2005-12-17 Optimization problems in practice are diverse and evolve over time, giving rise to - quirements both for ready-to-use optimization software packages and for optimization software libraries, which provide more or less adaptable building blocks for app- cation-specific software systems. In order to apply optimization methods to a new type of problem, corresponding models and algorithms have to be “coded” so that they are accessible to a computer. One way to achieve this step is the use of a mod- ing language. Such modeling systems provide an excellent interface between models and solvers, but only for a limited range of model types (in some cases, for example, linear) due, in part, to limitations imposed by the solvers. Furthermore, while m- eling systems especially for heuristic search are an active research topic, it is still an open question as to whether such an approach may be generally successful. Modeling languages treat the solvers as a “black box” with numerous controls. Due to variations, for example, with respect to the pursued objective or specific problem properties, - dressing real-world problems often requires special purpose methods. Thus, we are faced with the difficulty of efficiently adapting and applying appropriate methods to these problems. Optimization software libraries are intended to make it relatively easy and cost effective to incorporate advanced planning methods in application-specific software systems. A general classification provides a distinction between callable packages, nume- cal libraries, and component libraries. |
| lindo operations research: Groundwater Characterization, Management and Monitoring M. da Conceição Cunha, Luis Miguel Nunes, 2011 This title addresses the theoretical background necessary to accomplish planning and management of groundwater systems, and presents up-to-date applications of the decision-aid techniques in this field. |
| lindo operations research: Stochastic Programming Horand Gassmann, W. T. Ziemba, 2013 This book shows the breadth and depth of stochastic programming applications. All the papers presented here involve optimization over the scenarios that represent possible future outcomes of the uncertainty problems. The applications, which were presented at the 12th International Conference on Stochastic Programming held in Halifax, Nova Scotia in August 2010, span the rich field of uses of these models. The finance papers discuss such diverse problems as longevity risk management of individual investors, personal financial planning, intertemporal surplus management, asset management with benchmarks, dynamic portfolio management, fixed income immunization and racetrack betting. The production and logistics papers discuss natural gas infrastructure design, farming Atlantic salmon, prevention of nuclear smuggling and sawmill planning. The energy papers involve electricity production planning, hydroelectric reservoir operations and power generation planning for liquid natural gas plants. Finally, two telecommunication papers discuss mobile network design and frequency assignment problems. |
| lindo operations research: Integer Programming Laurence A. Wolsey, 2020-09-10 A PRACTICAL GUIDE TO OPTIMIZATION PROBLEMS WITH DISCRETE OR INTEGER VARIABLES, REVISED AND UPDATED The revised second edition of Integer Programming explains in clear and simple terms how to construct custom-made algorithms or use existing commercial software to obtain optimal or near-optimal solutions for a variety of real-world problems. The second edition also includes information on the remarkable progress in the development of mixed integer programming solvers in the 22 years since the first edition of the book appeared. The updated text includes information on the most recent developments in the field such as the much improved preprocessing/presolving and the many new ideas for primal heuristics included in the solvers. The result has been a speed-up of several orders of magnitude. The other major change reflected in the text is the widespread use of decomposition algorithms, in particular column generation (branch-(cut)-and-price) and Benders’ decomposition. The revised second edition: Contains new developments on column generation Offers a new chapter on Benders’ algorithm Includes expanded information on preprocessing, heuristics, and branch-and-cut Presents several basic and extended formulations, for example for fixed cost network flows Also touches on and briefly introduces topics such as non-bipartite matching, the complexity of extended formulations or a good linear program for the implementation of lift-and-project Written for students of integer/mathematical programming in operations research, mathematics, engineering, or computer science, Integer Programming offers an updated edition of the basic text that reflects the most recent developments in the field. |
| lindo operations research: Best Practices in Manufacturing Processes Jorge Luis García Alcaraz, Leonardo Rivera Cadavid, Rosa Guadalupe González-Ramírez, George Leal Jamil, Mario Gustavo Chong Chong, 2018-09-18 This book reports the best practices that companies established in Latin America are implementing in their manufacturing processes in order to generate high quality products and stay in the market. It lists the technologies, production and administrative philosophies that are being implemented, presenting a collection of successful cases of studies from Latin America. The book describes how the tools and techniques are being integrated, modified and combined to create new technical resources for assisting the decision making process for better economic performance in manufacturing companies. The efforts deployed for assisting the transformation of raw materials into products and services are described. The authors explain the main key success factors or drivers for success of each tool, technique or hybrid combination approach applied to solve manufacturing problems. |
| lindo operations research: Impacts of Recent Computer Advances on Operations Research Ramesh Sharda, 1989 |
| lindo operations research: OCaml Scientific Computing Liang Wang, Jianxin Zhao, Richard Mortier, 2022-05-26 This book is about the harmonious synthesis of functional programming and numerical computation. It shows how the expressiveness of OCaml allows for fast and safe development of data science applications. Step by step, the authors build up to use cases drawn from many areas of Data Science, Machine Learning, and AI, and then delve into how to deploy at scale, using parallel, distributed, and accelerated frameworks to gain all the advantages of cloud computing environments. To this end, the book is divided into three parts, each focusing on a different area. Part I begins by introducing how basic numerical techniques are performed in OCaml, including classical mathematical topics (interpolation and quadrature), statistics, and linear algebra. It moves on from using only scalar values to multi-dimensional arrays, introducing the tensor and Ndarray, core data types in any numerical computing system. It concludes with two more classical numerical computing topics, the solution of Ordinary Differential Equations (ODEs) and Signal Processing, as well as introducing the visualization module we use throughout this book. Part II is dedicated to advanced optimization techniques that are core to most current popular data science fields. We do not focus only on applications but also on the basic building blocks, starting with Algorithmic Differentiation, the most crucial building block that in turn enables Deep Neural Networks. We follow this with chapters on Optimization and Regression, also used in building Deep Neural Networks. We then introduce Deep Neural Networks as well as topic modelling in Natural Language Processing (NLP), two advanced and currently very active fields in both industry and academia. Part III collects a range of case studies demonstrating how you can build a complete numerical application quickly from scratch using Owl. The cases presented include computer vision and recommender systems. This book aims at anyone with a basic knowledge of functional programming and a desire to explore the world of scientific computing, whether to generally explore the field in the round, to build applications for particular topics, or to deep-dive into how numerical systems are constructed. It does not assume strict ordering in reading – readers can simply jump to the topic that interests them most. |
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LINDO Systems develops software tools for optimization modeling. We offer solvers and a featured environment for Linear Programming, Nonlinear Programming, Integer Programming …
Lindo | Spanish to English Translation - SpanishDictionary.com
Translate Lindo. See 11 authoritative translations of Lindo in English with example sentences, phrases and audio pronunciations.
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Downloads - LINDO
LINDO Systems develops software tools for optimization modeling. We offer solvers and a featured environment for Linear Programming, Nonlinear Programming, Integer Programming …
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LINDO Systems develops software tools for optimization modeling. We offer solvers and a featured environment for Linear Programming, Nonlinear Programming, Integer Programming …
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