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Pricing Based Revenue Management For Flexible Products On A Network
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Book Synopsis Pricing-Based Revenue Management for Flexible Products on a Network by : Dirk Sierag
Download or read book Pricing-Based Revenue Management for Flexible Products on a Network written by Dirk Sierag and published by . This book was released on 2016 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes and analyses a pricing-based revenue management model that allows flexible products on a network, with a non-trivial extension to group reservations. Under stochastic demand the problem can be solved using a dynamic programming formulation, though it suffers from the curse of dimensionality. The solution under deterministic demand gives an upper bound on the stochastic problem, and serves as a basis for two heuristics, which are asymptotically optimal. Numerical studies show that the heuristics perform well, even under uncertainty in demand. Moreover, neglecting flexible products can lead to substantial revenue loss.
Book Synopsis Pricing and Revenue Optimization by : Robert Phillips
Download or read book Pricing and Revenue Optimization written by Robert Phillips and published by Stanford University Press. This book was released on 2005-08-05 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first comprehensive introduction to the concepts, theories, and applications of pricing and revenue optimization. From the initial success of "yield management" in the commercial airline industry down to more recent successes of markdown management and dynamic pricing, the application of mathematical analysis to optimize pricing has become increasingly important across many different industries. But, since pricing and revenue optimization has involved the use of sophisticated mathematical techniques, the topic has remained largely inaccessible to students and the typical manager. With methods proven in the MBA courses taught by the author at Columbia and Stanford Business Schools, this book presents the basic concepts of pricing and revenue optimization in a form accessible to MBA students, MS students, and advanced undergraduates. In addition, managers will find the practical approach to the issue of pricing and revenue optimization invaluable. Solutions to the end-of-chapter exercises are available to instructors who are using this book in their courses. For access to the solutions manual, please contact [email protected].
Author :Michael Müller-Bungart Publisher :Springer Science & Business Media ISBN 13 :3540723161 Total Pages :307 pages Book Rating :4.5/5 (47 download)
Book Synopsis Revenue Management with Flexible Products by : Michael Müller-Bungart
Download or read book Revenue Management with Flexible Products written by Michael Müller-Bungart and published by Springer Science & Business Media. This book was released on 2007-09-18 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book analyzes revenue management (RM) problems with flexible products and RM in broadcasting companies. It presents models and methods that explicitly take the implications of flexibility into account. In addition, it contains descriptions of algorithms to generate stochastic demand data streams for general RM problems. To help readers with their own simulation studies, it provides an implementation as a Microsoft Windows executable file.
Book Synopsis Dynamic Programming Decomposition for Choice-Based Revenue Management with Flexible Products by : Sebastian Koch
Download or read book Dynamic Programming Decomposition for Choice-Based Revenue Management with Flexible Products written by Sebastian Koch and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We reconsider the stochastic dynamic program of revenue management with flexible products and customer choice behavior as proposed in the seminal paper by Gallego et al. [Gallego G, Iyengar G, Phillips R, Dubey A (2004) Managing flexible products on a network. Working paper, Columbia University, New York]. In the scientific literature on revenue management, as well as in practice, the prevailing strategy to operationalize dynamic programs is to decompose the network by resources and solve the resulting one-dimensional problems. However, up to now, these dynamic programming decomposition approaches have not been applicable to problems with flexible products, because the underlying state space is based on commitments rather than resources. In this paper, we contribute to the existing research by presenting an approach to operationalize revenue management with flexible products and customer choice in a dynamic programming environment. In particular, we propose a generic and formal procedure that transforms the original dynamic program with flexible products into an equivalent dynamic program with a resource-based state space. This reformulation renders the application of dynamic programming decomposition approaches possible. The procedure is based on Fourier-Motzkin elimination and is applicable to arbitrary network revenue management settings with regard to the considered network structure and the number and specifications of flexible products. Numerical experiments show a superior revenue performance of the new approach with average revenues close to the expected upper bound from the choice-based deterministic linear program (CDLP). Moreover, our reformulation improves revenues by up to 8% compared with an extended variant of a standard choice-based approach without flexible products that immediately assigns flexible products after sale.
Book Synopsis Online Learning and Pricing for Network Revenue Management with Reusable Resources by : Huiwen Jia
Download or read book Online Learning and Pricing for Network Revenue Management with Reusable Resources written by Huiwen Jia and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider a price-based network revenue management problem with multiple products and multiple reusable resources. Each randomly arriving customer requests a product (service) that needs to occupy a sequence of reusable resources (servers). We adopt an incomplete information setting where the firm does not know the price-demand function for each product and the goal is to dynamically set prices of all products to maximize the total expected revenue of serving customers. We propose novel batched bandit learning algorithms for finding near-optimal pricing policies, and show that they admit a near-optimal cumulative regret bound of $ tilde{O}(J sqrt{XT})$, where $J$, $X$, and $T$ are the numbers of products, candidate prices, and service periods, respectively. As part of our regret analysis, we develop the first finite-time mixing time analysis of an open network queueing system (i.e., the celebrated Jackson Network), which could be of independent interest. Our numerical studies show that the proposed approaches perform consistently well.
Book Synopsis Revenue Management and Pricing Analytics by : Guillermo Gallego
Download or read book Revenue Management and Pricing Analytics written by Guillermo Gallego and published by Springer. This book was released on 2019-08-14 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: “There is no strategic investment that has a higher return than investing in good pricing, and the text by Gallego and Topaloghu provides the best technical treatment of pricing strategy and tactics available.” Preston McAfee, the J. Stanley Johnson Professor, California Institute of Technology and Chief Economist and Corp VP, Microsoft. “The book by Gallego and Topaloglu provides a fresh, up-to-date and in depth treatment of revenue management and pricing. It fills an important gap as it covers not only traditional revenue management topics also new and important topics such as revenue management under customer choice as well as pricing under competition and online learning. The book can be used for different audiences that range from advanced undergraduate students to masters and PhD students. It provides an in-depth treatment covering recent state of the art topics in an interesting and innovative way. I highly recommend it." Professor Georgia Perakis, the William F. Pounds Professor of Operations Research and Operations Management at the Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts. “This book is an important and timely addition to the pricing analytics literature by two authors who have made major contributions to the field. It covers traditional revenue management as well as assortment optimization and dynamic pricing. The comprehensive treatment of choice models in each application is particularly welcome. It is mathematically rigorous but accessible to students at the advanced undergraduate or graduate levels with a rich set of exercises at the end of each chapter. This book is highly recommended for Masters or PhD level courses on the topic and is a necessity for researchers with an interest in the field.” Robert L. Phillips, Director of Pricing Research at Amazon “At last, a serious and comprehensive treatment of modern revenue management and assortment optimization integrated with choice modeling. In this book, Gallego and Topaloglu provide the underlying model derivations together with a wide range of applications and examples; all of these facets will better equip students for handling real-world problems. For mathematically inclined researchers and practitioners, it will doubtless prove to be thought-provoking and an invaluable reference.” Richard Ratliff, Research Scientist at Sabre “This book, written by two of the leading researchers in the area, brings together in one place most of the recent research on revenue management and pricing analytics. New industries (ride sharing, cloud computing, restaurants) and new developments in the airline and hotel industries make this book very timely and relevant, and will serve as a critical reference for researchers.” Professor Kalyan Talluri, the Munjal Chair in Global Business and Operations, Imperial College, London, UK.
Book Synopsis The Theory and Practice of Revenue Management by : Kalyan T. Talluri
Download or read book The Theory and Practice of Revenue Management written by Kalyan T. Talluri and published by Springer Science & Business Media. This book was released on 2006-02-21 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: Revenue management (RM) has emerged as one of the most important new business practices in recent times. This book is the first comprehensive reference book to be published in the field of RM. It unifies the field, drawing from industry sources as well as relevant research from disparate disciplines, as well as documenting industry practices and implementation details. Successful hardcover version published in April 2004.
Book Synopsis Pricing and Revenue Optimization by : Robert L. Phillips
Download or read book Pricing and Revenue Optimization written by Robert L. Phillips and published by Stanford Business Books. This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Background -- Introduction to pricing and revenue optimization -- Models of demand -- Estimating price response -- Optimization -- Price differentiation -- Pricing with constrained supply -- Revenue management -- Capacity allocation -- Network management -- Overbooking -- Markdown management -- Customized pricing -- Behavioral economics and pricing.
Book Synopsis Approximate Dynamic Programming by : Warren B. Powell
Download or read book Approximate Dynamic Programming written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2007-10-05 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete and accessible introduction to the real-world applications of approximate dynamic programming With the growing levels of sophistication in modern-day operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. Approximate Dynamic Programming is a result of the author's decades of experience working in large industrial settings to develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. This groundbreaking book uniquely integrates four distinct disciplines—Markov design processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully model and solve a wide range of real-life problems using the techniques of approximate dynamic programming (ADP). The reader is introduced to the three curses of dimensionality that impact complex problems and is also shown how the post-decision state variable allows for the use of classical algorithmic strategies from operations research to treat complex stochastic optimization problems. Designed as an introduction and assuming no prior training in dynamic programming of any form, Approximate Dynamic Programming contains dozens of algorithms that are intended to serve as a starting point in the design of practical solutions for real problems. The book provides detailed coverage of implementation challenges including: modeling complex sequential decision processes under uncertainty, identifying robust policies, designing and estimating value function approximations, choosing effective stepsize rules, and resolving convergence issues. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, Approximate Dynamic Programming: Models complex, high-dimensional problems in a natural and practical way, which draws on years of industrial projects Introduces and emphasizes the power of estimating a value function around the post-decision state, allowing solution algorithms to be broken down into three fundamental steps: classical simulation, classical optimization, and classical statistics Presents a thorough discussion of recursive estimation, including fundamental theory and a number of issues that arise in the development of practical algorithms Offers a variety of methods for approximating dynamic programs that have appeared in previous literature, but that have never been presented in the coherent format of a book Motivated by examples from modern-day operations research, Approximate Dynamic Programming is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The clear and precise presentation of the material makes this an appropriate text for advanced undergraduate and beginning graduate courses, while also serving as a reference for researchers and practitioners. A companion Web site is available for readers, which includes additional exercises, solutions to exercises, and data sets to reinforce the book's main concepts.
Book Synopsis Efficiency and Performance Guarantees for Choice-Based Network Revenue Management Problems with Flexible Products by : Wang Chi Cheung
Download or read book Efficiency and Performance Guarantees for Choice-Based Network Revenue Management Problems with Flexible Products written by Wang Chi Cheung and published by . This book was released on 2016 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider the choice-based network revenue management problem (NRM). The LP relaxation, Choice-based Deterministic Linear Program (CDLP-P), has been proposed to mitigate the curse of dimensionality of the choice-based NRM. Despite the importance of CDLP-P, there is no polynomial time algorithm for solving CDLP-P for general choice models. Moreover, most heuristics for solving CDLP-P require solving the underlying Single Period Problem (SPP), which could be NP-hard. We propose the Potential Based algorithm (PB) that solves CDLP-P to near optimality with provable efficiency, assuming the ability to solve the underlying SPP approximately. In particular, PB implies polynomial time algorithms for approximating CDLP-P for a variety of choice models, such as Nested Logit, Mixed Logit and Markov Chain models, to near optimality.We also propose the Approximate Column Generation heuristic (ACG), which generalizes the classical Column Generation heuristic, and returns a near optimal solution to CDLP-P at termination. Different from PB, ACG is not known to be provably efficient. Finally, building on the tractability result, we design an earning-while-learning policy for the online NRM problem under an MultiNomial Logit choice model with unknown parameters. The policy runs in polynomial time, and achieves a sublinear regret.
Book Synopsis Fair Revenue Sharing Mechanisms for Strategic Passenger Airline Alliances by : Demet Çetiner
Download or read book Fair Revenue Sharing Mechanisms for Strategic Passenger Airline Alliances written by Demet Çetiner and published by Springer Science & Business Media. This book was released on 2013-04-03 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: A major problem arising in airline alliances is to design allocation mechanisms determining how the revenue of a product should be shared among the airlines. The nucleolus is a concept of cooperative game theory that provides solutions for allocating the cost or benefit of a cooperation. This work provides fair revenue proportions for the airline alliances based on the nucleolus, which assumes a centralized decision making system. The proposed mechanism is used as a benchmark to evaluate the fairness of the revenue sharing mechanisms, where the alliance partners behave selfishly. Additionally, a new selfish revenue allocation rule is developed that improves the performance of the existing methods.
Book Synopsis Global Operations Strategy by : Yeming Gong
Download or read book Global Operations Strategy written by Yeming Gong and published by Springer Science & Business Media. This book was released on 2013-07-01 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: While many business schools are teaching Global Operations Strategy with self-made teaching materials, there are no such textbooks. Combining practical approaches with detailed theoretical underpinnings, this book provides theories, tools, frameworks, and techniques for global operations strategy, and brings real world perspectives to students and managers. Each chapter includes definition of key terms, introduction of fundamental theories, several short case examples, one long new case to explain the associated theories, and recommended further reading.
Book Synopsis Applications in Statistical Computing by : Nadja Bauer
Download or read book Applications in Statistical Computing written by Nadja Bauer and published by Springer Nature. This book was released on 2019-10-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.
Book Synopsis Global Supply Chain and Operations Management by : Dmitry Ivanov
Download or read book Global Supply Chain and Operations Management written by Dmitry Ivanov and published by Springer Nature. This book was released on 2021-11-19 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of this textbook comprehensively discusses global supply chain and operations management (SCOM), combining value creation networks and interacting processes. It focuses on operational roles within networks and presents the quantitative and organizational methods needed to plan and control the material, information, and financial flows in supply chains. Each chapter begins with an introductory case study, while numerous examples from various industries and services help to illustrate the key concepts. The book explains how to design operations and supply networks and how to incorporate suppliers and customers. It examines how to balance supply and demand, a core aspect of tactical planning, before turning to the allocation of resources to meet customer needs. In addition, the book presents state-of-the-art research reflecting the lessons learned from the COVID-19 pandemic, and emerging, fast-paced developments in the digitalization of supply chain and operations management. Providing readers with a working knowledge of global supply chain and operations management, with a focus on bridging the gap between theory and practice, this textbook can be used in core, specialized, and advanced classes alike. It is intended for a broad range of students and professionals in supply chain and operations management.
Book Synopsis Advanced Studies in Behaviormetrics and Data Science by : Tadashi Imaizumi
Download or read book Advanced Studies in Behaviormetrics and Data Science written by Tadashi Imaizumi and published by Springer Nature. This book was released on 2020-04-17 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and related areas of data science, including analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, visualization of such data, multivariate statistical methods, analysis of asymmetric relational data, and various applications to real data. In addition to theoretical and methodological results, it also shows how to apply the proposed methods to a variety of problems, for example in consumer behavior, decision making, marketing data, and social network structures. Moreover, it discuses methodological aspects and applications in a wide range of areas, such as behaviormetrics; behavioral science; psychology; and marketing, management and social sciences. Combining methodological advances with real-world applications collected from a variety of research fields, the book is a valuable resource for researchers and practitioners, as well as for applied statisticians and data analysts.
Book Synopsis Algorithms from and for Nature and Life by : Berthold Lausen
Download or read book Algorithms from and for Nature and Life written by Berthold Lausen and published by Springer Science & Business Media. This book was released on 2013-08-28 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides approaches and solutions to challenges occurring at the interface of research fields such as, e.g., data analysis, data mining and knowledge discovery, computer science, operations research, and statistics. In addition to theory-oriented contributions various application areas are included. Moreover, traditional classification research directions concerning network data, graphs, and social relationships as well as statistical musicology describe examples for current interest fields tackled by the authors. The book comprises a total of 55 selected papers presented at the Joint Conference of the German Classification Society (GfKl), the German Association for Pattern Recognition (DAGM), and the Symposium of the International Federation of Classification Societies (IFCS) in 2011.
Book Synopsis Network Optimization by : Julia Pahl
Download or read book Network Optimization written by Julia Pahl and published by Springer Science & Business Media. This book was released on 2011-06-03 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Conference on Network Optimization, INOC 2011, held in Hamburg, Germany, in June 2011. The 65 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers highlight recent developments in network optimization and are organized in the following topical sections: theoretical problems, uncertainty, graph theory and network design; network flows; routing and transportation; and further optimization problems and applications (energy oriented network design, telecom applications, location, maritime shipping, and graph theory).
