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A new approach to dynamic allocation and pricing that blends dynamic paradigms from the operations research and management science literature with classical mechanism design methods. Dynamic allocation and pricing problems occur in numerous frameworks, including the pricing of seasonal goods in retail, the allocation of a fixed inventory in a given period of time, and the assignment of personnel to incoming tasks. Although most of these problems deal with issues treated in the mechanism design literature, the modern revenue management (RM) literature focuses instead on analyzing properties of restricted classes of allocation and pricing schemes. In this book, Alex Gershkov and Benny Moldovanu propose an approach to optimal allocations and prices based on the theory of mechanism design, adapted to dynamic settings. Drawing on their own recent work on the topic, the authors describe a modern theory of RM that blends the elegant dynamic models from the operations research (OR), management science, and computer science literatures with techniques from the classical mechanism design literature. Illustrating this blending of approaches, they start with well-known complete information, nonstrategic dynamic models that yield elegant explicit solutions. They then add strategic agents that are privately informed and then examine the consequences of these changes on the optimization problem of the designer. Their sequential modeling of both nonstrategic and strategic logic allows a clear picture of the delicate interplay between dynamic trade-offs and strategic incentives. Topics include the sequential assignment of heterogeneous objects, dynamic revenue optimization with heterogeneous objects, revenue maximization in the stochastic and dynamic knapsack model, the interaction between learning about demand and dynamic efficiency, and dynamic models with long-lived, strategic agents.
This book develops allocation mechanisms that aim to ensure an efficient resource allocation in modern IT-services. Recent methods of artificial intelligence, such as neural networks and reinforcement learning, and nature-oriented optimization methods, such as genetic algorithms and simulated annealing, are advanced and applied to allocation processes in distributed IT-infrastructures, or grid systems.
The overwhelming majority of bugs and crashes in computer programming stem from problems of memory access, allocation, or deallocation. Such memory related errors are also notoriously difficult to debug. Yet the role that memory plays in C and C++ programming is a subject often overlooked in courses and in books because it requires specialised knowledge of operating systems, compilers, computer architecture in addition to a familiarity with the languages themselves. Most professional programmers learn entirely through experience of the trouble it causes. This 2004 book provides students and professional programmers with a concise yet comprehensive view of the role memory plays in all aspects of programming and program behaviour. Assuming only a basic familiarity with C or C++, the author describes the techniques, methods, and tools available to deal with the problems related to memory and its effective use.
This is an advanced text on the theory of forward and futures markets which aims at providing readers with a comprehensive knowledge of how prices are established and evolve over time, what optimal strategies one can expect from the participants, what characterizes such markets and what major theoretical and practical differences distinguish futures from forward contracts. It should be of interest to students (majoring in finance with quantitative skills) academics (both theoreticians and empiricists), practitioners, and regulators.
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.
Today’s modern portfolio theory is not your father’s MPT. It has undergone many changes in the past fifty years. Indeed, a new understanding of MPT has emerged, one that has a significant impact on managing asset allocation—especially in today’s turbulent markets. Dynamic Asset Allocation interprets and integrates the developments in modern portfolio theory: from the efficient-market hypothesis and indexing of decades past to strategies for building winning portfolios today. The book is filled with practical, hands-on advice for investors, including guidance on approaching investment as a risk-management task.
Using techniques developed in the classroom at America Online's Programmer's University, Michael Daconta deftly pilots programmers through the intricacies of the two most difficult aspects of C++ programming: pointers and dynamic memory management. Written by a programmer for programmers, this no-nonsense, nuts-and-bolts guide shows you how to fully exploit advanced C++ programming features, such as creating class-specific allocators, understanding references versus pointers, manipulating multidimensional arrays with pointers, and how pointers and dynamic memory are the core of object-oriented constructs like inheritance, name-mangling, and virtual functions. Covers all aspects of pointers including: pointer pointers, function pointers, and even class member pointers Over 350 source code functions—code on every topic OOP constructs dissected and implemented in C Interviews with leading C++ experts Valuable money-saving coupons on developer products Free source code disk Disk includes: Reusable code libraries—over 350 source code functions you can use to protect and enhance your applications Memory debugger Read C++ Pointers and Dynamic Memory Management and learn how to combine the elegance of object-oriented programming with the power of pointers and dynamic memory!
A comprehensive overview of networks and economic design, presenting models and results drawn from economics, operations research, and computer science; with examples and exercises. This book explores networks and economic design, focusing on the role played by allocation rules (revenue and cost-sharing schemes) in creating and sustaining efficient network solutions. It takes a normative approach, seeking economically efficient network solutions sustained by distributional fairness, and considers how different ways of allocating liability affect incentives for network usage and development. The text presents an up-to-date overview of models and results currently scattered over several strands of literature, drawing on economics, operations research, and computer science. The book's analysis of allocation problems includes such classic models from combinatorial optimization as the minimum cost spanning tree and the traveling salesman problem. It examines the planner's ability to design mechanisms that will implement efficient network structures, both in large decentralized networks and when there is user-agent information asymmetry. Offering systematic theoretical analyses of various compelling allocation rules in cases of fixed network structures as well as discussions of network design problems, the book covers such topics as tree-structured distribution systems, routing games, organizational hierarchies, the “price of anarchy,” mechanism design, and efficient implementation. Appropriate as a reference for practitioners in network regulation and the network industry or as a text for graduate students, the book offers numerous illustrative examples and end-of-chapter exercises that highlight the concepts and methods presented.
This is the first comprehensive book on the AIMD algorithm, the most widely used method for allocating a limited resource among competing agents without centralized control. The authors offer a new approach that is based on positive switched linear systems. It is used to develop most of the main results found in the book, and fundamental results on stochastic switched nonnegative and consensus systems are derived to obtain these results. The original and best known application of the algorithm is in the context of congestion control and resource allocation on the Internet, and readers will find details of several variants of the algorithm in order of increasing complexity, including deterministic, random, linear, and nonlinear versions. In each case, stability and convergence results are derived based on unifying principles. Basic and fundamental properties of the algorithm are described, examples are used to illustrate the richness of the resulting dynamical systems, and applications are provided to show how the algorithm can be used in the context of smart cities, intelligent transportation systems, and the smart grid.