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Optimisation Of Production Under Uncertainty
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Book Synopsis Optimisation of Production Under Uncertainty by : Svend Rasmussen
Download or read book Optimisation of Production Under Uncertainty written by Svend Rasmussen and published by Springer Science & Business Media. This book was released on 2011-07-23 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a short review of the classical approach to planning and decision making under uncertainty. It further explains the concept of state-contingent goods, and it extends earlier work on the state-contingent approach to describing production under uncertainty to the problems involved in optimising production under uncertainty.
Book Synopsis Optimization of Temporal Networks under Uncertainty by : Wolfram Wiesemann
Download or read book Optimization of Temporal Networks under Uncertainty written by Wolfram Wiesemann and published by Springer Science & Business Media. This book was released on 2012-01-04 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many decision problems in Operations Research are defined on temporal networks, that is, workflows of time-consuming tasks whose processing order is constrained by precedence relations. For example, temporal networks are used to model projects, computer applications, digital circuits and production processes. Optimization problems arise in temporal networks when a decision maker wishes to determine a temporal arrangement of the tasks and/or a resource assignment that optimizes some network characteristic (e.g. the time required to complete all tasks). The parameters of these optimization problems (e.g. the task durations) are typically unknown at the time the decision problem arises. This monograph investigates solution techniques for optimization problems in temporal networks that explicitly account for this parameter uncertainty. We study several formulations, each of which requires different information about the uncertain problem parameters.
Book Synopsis Production Economics by : Svend Rasmussen
Download or read book Production Economics written by Svend Rasmussen and published by Springer Science & Business Media. This book was released on 2012-08-04 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the basic theory of how, what and when firms should produce to maximise profits. Based on the neoclassical theory of the firm presented in most general microeconomic textbooks, it extends the general treatment and focuses on the application of the theory to specific problems that the firm faces when making production decisions to maximise profits. Increasing level of government regulation and the use of specialised and often very expensive equipment in modern production motivates the following focus areas: 1) How to optimise production under restrictions., 2) Treatment of fixed inputs and the process of input fixation, 3) Optimisation of production over time, 4) Linear and Mixed Integer Programming as tools for optimisation in practice. This updated second edition includes a more comprehensive introduction to the theory of decision making under risk and uncertainty as well as a new chapter on how to use linear programming to generate the supply function of the firm.
Book Synopsis Optimization with Uncertainty in Pork Production by : Stephanie Cara Rutten-Ramos
Download or read book Optimization with Uncertainty in Pork Production written by Stephanie Cara Rutten-Ramos and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Supply Chain Optimization Under Uncertainty by : Barrie Michael Cole
Download or read book Supply Chain Optimization Under Uncertainty written by Barrie Michael Cole and published by Vernon Press. This book was released on 2015-09-15 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on cutting-edge research, this book proposes a new 'Supply Chain Optimization under Uncertainty', technology. Its application can bring many proven benefits to supply chain entities, any associated service providers, and, of course, the customers. The technology can provide the best design and operating solution for a Supply Chain Network (SCN) that is subject to any prevailing conditions of Operational Uncertainty (OU). A SCN is defined as a network of production facilities, distribution centers and retail sales outlets. OU is defined as any relevant combination of i) multiple process objectives e.g. a business needs to maximize operating profits and to minimize inventory levels, ii) fuzziness (, or >=) e.g. sales
Book Synopsis Robust Optimization of a Multi-period Production Planning Problem Under Uncertainty by : Michal Rozenblit
Download or read book Robust Optimization of a Multi-period Production Planning Problem Under Uncertainty written by Michal Rozenblit and published by . This book was released on 2010 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry by : Víctor M. Albornoz
Download or read book Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry written by Víctor M. Albornoz and published by Springer Nature. This book was released on with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Supply Chain Optimization under Uncertainty by : Barrie M. Cole
Download or read book Supply Chain Optimization under Uncertainty written by Barrie M. Cole and published by Vernon Press. This book was released on 2014-12-15 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on cutting-edge research, this book proposes a new 'Supply Chain Optimization under Uncertainty’, technology. Its application can bring many proven benefits to supply chain entities, any associated service providers, and, of course, the customers. The technology can provide the best design and operating solution for a Supply Chain Network (SCN) that is subject to any prevailing conditions of Operational Uncertainty (OU). A SCN is defined as a network of production facilities, distribution centers and retail sales outlets. OU is defined as any relevant combination of i) multiple process objectives e.g. a business needs to maximize operating profits and to minimize inventory levels, ii) fuzziness (<, <=, >, or >=) e.g. sales <= 1500 t/mth and iii) probability e.g. sale of fertilizer is dependent on probabilistic rainfall. Following this method always enables the determination of realistic optimum supply chain solutions, since the effects of any operational uncertainties are always provided for. The book is arranged in two parts. The first part covers the theory and recent research into supply chain optimization under uncertainty. The second part documents the application of the newly proposed technology to an agricultural fertilizer’s (NPK, South Africa) supply chain.
Book Synopsis An Intertemporal Interspatial Optimization Problem Under Uncertainty by : Michael A. Moses
Download or read book An Intertemporal Interspatial Optimization Problem Under Uncertainty written by Michael A. Moses and published by . This book was released on 1965 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Allocation under Uncertainty: Equilibrium and Optimality by : Jacques H Drèze
Download or read book Allocation under Uncertainty: Equilibrium and Optimality written by Jacques H Drèze and published by Springer. This book was released on 1965-01-01 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modern Optimization Methods for Decision Making Under Risk and Uncertainty by : Alexei A. Gaivoronski
Download or read book Modern Optimization Methods for Decision Making Under Risk and Uncertainty written by Alexei A. Gaivoronski and published by CRC Press. This book was released on 2023-10-06 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book comprises original articles on topical issues of risk theory, rational decision making, statistical decisions, and control of stochastic systems. The articles are the outcome of a series international projects involving the leading scholars in the field of modern stochastic optimization and decision making. The structure of stochastic optimization solvers is described. The solvers in general implement stochastic quasi-gradient methods for optimization and identification of complex nonlinear models. These models constitute an important methodology for finding optimal decisions under risk and uncertainty. While a large part of current approaches towards optimization under uncertainty stems from linear programming (LP) and often results in large LPs of special structure, stochastic quasi-gradient methods confront nonlinearities directly without need of linearization. This makes them an appropriate tool for solving complex nonlinear problems, concurrent optimization and simulation models, and equilibrium situations of different types, for instance, Nash or Stackelberg equilibrium situations. The solver finds the equilibrium solution when the optimization model describes the system with several actors. The solver is parallelizable, performing several simulation threads in parallel. It is capable of solving stochastic optimization problems, finding stochastic Nash equilibria, and of composite stochastic bilevel problems where each level may require the solution of stochastic optimization problem or finding Nash equilibrium. Several complex examples with applications to water resources management, energy markets, pricing of services on social networks are provided. In the case of power system, regulator makes decision on the final expansion plan, considering the strategic behavior of regulated companies and coordinating the interests of different economic entities. Such a plan can be an equilibrium − a planned decision where a company cannot increase its expected gain unilaterally.
Book Synopsis Optimizing Production Under Uncertainty by : Svend Rasmussen
Download or read book Optimizing Production Under Uncertainty written by Svend Rasmussen and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Uncertainty Management in Simulation-Optimization of Complex Systems by : Gabriella Dellino
Download or read book Uncertainty Management in Simulation-Optimization of Complex Systems written by Gabriella Dellino and published by Springer. This book was released on 2015-06-29 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together — as chapter contributors — researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors’ goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.
Book Synopsis Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems by : Son Duy Dao
Download or read book Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems written by Son Duy Dao and published by Springer. This book was released on 2017-12-27 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems. It also describes a robust genetic algorithm for production scheduling in VCIM systems. The model, which is the most comprehensive of its kind to date, is not only capable of supporting collaborative shipment scheduling and handling multiple product orders simultaneously, but also helps cope with multiple objective functions under uncertainties. In turn, the genetic algorithm, characterised by an innovative algorithm structure, chromosome encoding, crossover and mutation, is capable of searching for optimal/suboptimal solutions to the complex optimisation problem in the VCIM production- scheduling model described. Lastly, the effectiveness of the proposed approach is verified in a comprehensive case study.
Book Synopsis Optimization of Production Allocation Under Price Uncertainty by : Adbulwahab Abdullatif Bukhari
Download or read book Optimization of Production Allocation Under Price Uncertainty written by Adbulwahab Abdullatif Bukhari and published by . This book was released on 2011 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Allocating production volumes across a portfolio of producing assets is a complex optimization problem. Each producing asset possesses different technical attributes (e.g. crude type), facility constraints, and costs. In addition, there are corporate objectives and constraints (e.g. contract delivery requirements). While complex, such a problem can be specified and solved using conventional deterministic optimization methods. However, there is often uncertainty in many of the inputs, and in these cases the appropriate approach is neither obvious nor straightforward. One of the major uncertainties in the oil and gas industry is the commodity price assumption(s). This paper investigates this problem in three major sections: (1) We specify an integrated stochastic optimization model that solves for the optimal production allocation for a portfolio of producing assets when there is uncertainty in commodity prices, (2) We then compare the solutions that result when different price models are used, and (3) We perform a value of information analysis to estimate the value of more accurate price models. The results show that the optimum production allocation is a function of the price model assumptions. However, the differences between models are minor, and thus the value of choosing the "correct" price model, or similarly of estimating a more accurate model, is small. This work falls in the emerging research area of decision-oriented assessments of information value.
Book Synopsis Robust Optimization by : Aharon Ben-Tal
Download or read book Robust Optimization written by Aharon Ben-Tal and published by Princeton University Press. This book was released on 2009-08-10 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
Book Synopsis The Analytics of Uncertainty and Information by : Sushil Bikhchandani
Download or read book The Analytics of Uncertainty and Information written by Sushil Bikhchandani and published by Cambridge University Press. This book was released on 2013-08-12 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: There has been explosive progress in the economic theory of uncertainty and information in the past few decades. This subject is now taught not only in departments of economics but also in professional schools and programs oriented toward business, government and administration, and public policy. This book attempts to unify the subject matter in a simple, accessible manner. Part I of the book focuses on the economics of uncertainty; Part II examines the economics of information. This revised and updated second edition places a greater focus on game theory. New topics include posted-price markets, mechanism design, common-value auctions, and the one-shot deviation principle for repeated games.
