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Call Center Optimization
This book gives an accessible overview of the role and potential of mathematical optimization in call centers. It deals extensively with all aspects of workforce management, but also with topics such as call routing and the scheduling of multiple channels. It does so without going into the mathematics, but by focusing on understanding its consequences. This way the reader will get familiar with workload forecasting, the Erlang formulas, simulation, and so forth, and learn how to improve call center performance using it. The book is primarily meant for call center professionals involved in planning and business analytics, but also call center managers and researchers will find it useful. There is an accompanying website which contains several online calculators.
An Introduction to Business Analytics
Business Analytics (BA) is about turning data into decisions. This book covers the full range of BA topics, including statistics, machine learning and optimization, in a way that makes them accessible to a broader audience. Decision makers will gain enough insight into the subject to have meaningful discussions with machine learning specialists, and those starting out as data scientists will benefit from an overview of the field and take their first steps as business analytics specialist. Through this book and the various exercises included, you will be equipped with an understanding of BA, while learning R, a popular tool for statistics and machine learning.
Monotonicity in Markov Reward and Decision Chains
Monotonicity in Markov Reward and Decision Chains: Theory and Applications focuses on monotonicity results for dynamic systems that take values in the natural numbers or in more-dimensional lattices. The results are mostly formulated in terms of controlled queueing systems, but there are also applications to maintenance systems, revenue management, and so forth. The focus is on results that are obtained by inductively proving properties of the dynamic programming value function. A framework is provided for using this method that unifies results obtained for different models. The author also provides a comprehensive overview of the results that can be obtained through it, in which he discusses not only (partial) characterizations of optimal policies but also applications of monotonicity to optimization problems and the comparison of systems. Monotonicity in Markov Reward and Decision Chains: Theory and Applications is an invaluable resource for anyone planning or conducting research in this particular area. The essentials of the topic are presented in an accessible manner and an extensive bibliography guides towards further reading.
Asymptotic Statistics
This book is an introduction to the field of asymptotic statistics. The treatment is both practical and mathematically rigorous. In addition to most of the standard topics of an asymptotics course, including likelihood inference, M-estimation, the theory of asymptotic efficiency, U-statistics, and rank procedures, the book also presents recent research topics such as semiparametric models, the bootstrap, and empirical processes and their applications. The topics are organized from the central idea of approximation by limit experiments, which gives the book one of its unifying themes. This entails mainly the local approximation of the classical i.i.d. set up with smooth parameters by location experiments involving a single, normally distributed observation. Thus, even the standard subjects of asymptotic statistics are presented in a novel way. Suitable as a graduate or Master s level statistics text, this book will also give researchers an overview of the latest research in asymptotic statistics.
Advances in Service Science
This volume offers the state-of-the-art research and developments in service science and related research, education and practice areas. It showcases emerging technology and applications in fields including healthcare, information technology, transportation, sports, logistics, and public services. Regardless of size and service, a service organization is a service system. Because of the socio-technical nature of a service system, a systems approach must be adopted to design, develop, and deliver services, aimed at meeting end users' both utilitarian and socio-psychological needs. Effective understanding of service and service systems often requires combining multiple methods to consider how interactions of people, technology, organizations, and information create value under various conditions. The papers in this volume highlight ways to approach such technical challenges in service science and are based on submissions from the 2018 INFORMS International Conference on Service Science.
Methoden en modellen voor zorglogistiek
Dit boek behandelt op een toegankelijke manier de meer rekenkundige kant van zorglogistiek. Alle aspecten komen aan de orde, van data analyse tot modellen voor capaciteitsplanning, zonder wiskundige formules, op een manier die aansluit bij de intuïtie van de lezer. In de stof en de voorbeelden komt de volle breedte van de zorg aan bod. Dat maakt dit boek geschikt voor HBO en WO studenten in alle zorggerelateerde studierichtingen, en ook voor zorgprofessionals die zich willen bekwamen op het gebied van zorglogistiek. Bij dit boek hoort een website waar veel van de behandelde rekenmethodes kunnen worden uitgeprobeerd.
Why People Do the Things They Do
A unique and comprehensive book by leading researchers looking at motivation and volition. How can we motivate students, patients, employees, and athletes? What helps us achieve our goals, improve our well-being, and grow as human beings? These issues, which relate to motivation and volition, are familiar to everyone who faces the challenges of everyday life. This comprehensive book by leading international scholars provides integrative perspectives on motivation and volition that build on the work of German psychologist Julius Kuhl. The first part of the book examines the historical trail of the European and American research traditions of motivation and volition and their integration in Ku...
Markov Decision Processes in Practice
This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization. MDP allows users to develop and formally support approximate and simple decision rules, and this book showcases state-of-the-art applications in which MDP was key to the solution approach. The book is divided into six parts. Part 1 is devoted to the state-of-the-art theoretical foundation of MDP, including approximate methods such as policy improvement, successive approximation and infinite state spaces as well as an instructive chapter on Approximate Dynamic Programming. It then continues with five parts of specific and non-exhaustive application areas. Part 2 covers MDP healthcare appl...
High Performance Computing - HiPC 2004
Annotation. This book constitutes the refereed proceedings of the 11th International Conference on High-Performance Computing, HiPC 2004, held in Bangalore, India in December 2004. The 48 revised full papers presented were carefully reviewed and selected from 253 submissions. The papers are organized in topical sections on wireless network management, compilers and runtime systems, high performance scientific applications, peer-to-peer and storage systems, high performance processors and routers, grids and storage systems, energy-aware and high-performance networking, and distributed algorithms.
Choice-set Demand in Revenue Management: Unconstraining, Forecasting and Optimization
Focus on Profit! Maximize your revenue and profit by understanding and considering your customers’ buying behavior. How price sensitive are your customers? What are their preferences? How strong are the competitor influences or cannibalization effects in your own product portfolio? These questions must be answered analytically, in order to obtain a quantitative understanding of the customers’ choice process and hence a clear picture of the demand in the market. We propose the notion of choice-sets as our model for the customers’ preferences and buying decisions. The unconstraining is the related process which extracts demand information with choice behavior from product sales data. Once, we obtained the information of current and past demand data, the immediate next step is the demand forecasting. Finally, with an accurate estimate of the future demand, we continue with the optimization process, to derive optimal sales controls and pricing actions which maximize the overall revenue or profit.
