Author: Hao Yuan Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
We consider a periodic-review single-product inventory system with fixed cost under censored demand. Under full demand distributional information, it is well-known that the celebrated $(s,S)$ policy is optimal. In this paper, we assume the firm does not know the demand distribution a priori, and makes adaptive inventory ordering decision in each period based only on the past sales (a.k.a. censored demand) data. The standard performance measure is regret, which is the cost difference between a feasible learning algorithm and the clairvoyant (full-information) benchmark. Compared with prior literature, the key difficulty of this problem lies in the loss of joint convexity of the objective function, due to the presence of fixed cost. We develop a nonparametric learning algorithm termed the $( delta, S)$ policy that combines the powers of stochastic gradient descent, bandit controls, and simulation-based methods in a seamless and non-trivial fashion. We prove that the cumulative regret is $O( log T sqrt{T})$, which is provably tight up to a logarithmic factor. We also develop several technical results that are of independent interest. We believe that the framework developed could be widely applied to learning other important stochastic systems with partial convexity in the objectives.
Author: Jing-Sheng J. Song Publisher: Edward Elgar Publishing ISBN: 180037710X Category : Technology & Engineering Languages : en Pages : 565
Book Description
This comprehensive Handbook provides an overview of state-of-the-art research on quantitative models for inventory management. Despite over half a century’s progress, inventory management remains a challenge, as evidenced by the recent Covid-19 pandemic. With an expanse of world-renowned inventory scholars from major international research universities, this Handbook explores key areas including mathematical modelling, the interplay of inventory decisions and other business decisions and the unique challenges posed to multiple industries.
Author: Xi Chen Publisher: Springer Nature ISBN: 3031019261 Category : Business & Economics Languages : en Pages : 444
Book Description
This book examines recent developments in Operations Management, and focuses on four major application areas: dynamic pricing, assortment optimization, supply chain and inventory management, and healthcare operations. Data-driven optimization in which real-time input of data is being used to simultaneously learn the (true) underlying model of a system and optimize its performance, is becoming increasingly important in the last few years, especially with the rise of Big Data.
Author: Steven Nahmias Publisher: Springer Science & Business Media ISBN: 1441979999 Category : Business & Economics Languages : en Pages : 89
Book Description
A perishable item is one that has constant utility up until an expiration date (which may be known or uncertain), at which point the utility drops to zero. This includes many types of packaged foods such as milk, cheese, processed meats, and canned goods. It also includes virtually all pharmaceuticals and photographic film, as well as whole blood supplies. This book is the first devoted solely to perishable inventory systems. The book’s ten chapters first cover the preliminaries of periodic review versus continuous review and look at a one-period newsvendor perishable inventory model. The author moves to the basic multiperiod dynamic model, and then considers the extensions of random lifetime, inclusion of a set-up cost, and multiproduct models of perishables. A chapter on continuous review models looks at one-for-one policies, models with zero lead time, optimal policies with positive lead time, and an alternative approach. Additional chapters present material on approximate order policies, inventory depletion management, and deterministic models, including the basic EOQ model with perishability and the dynamic deterministic model with perishability. Finally, chapters explore decaying inventories, queues with impatient customers, and blood bank inventory control. Anyone researching perishable inventory systems will find much to work with here. Practitioners and consultants will also now have a single well-referenced source of up-to-date information to work with.
Author: Joanne Quinn Publisher: Corwin Press ISBN: 1544385404 Category : Education Languages : en Pages : 297
Book Description
The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Dive Into Deep Learning: Tools for Engagement is rich with resources educators need to construct and drive meaningful deep learning experiences in order to develop the kind of mindset and know-how that is crucial to becoming a problem-solving change agent in our global society. Designed in full color, this easy-to-use guide is loaded with tools, tips, protocols, and real-world examples. It includes: • A framework for deep learning that provides a pathway to develop the six global competencies needed to flourish in a complex world — character, citizenship, collaboration, communication, creativity, and critical thinking. • Learning progressions to help educators analyze student work and measure progress. • Learning design rubrics, templates and examples for incorporating the four elements of learning design: learning partnerships, pedagogical practices, learning environments, and leveraging digital. • Conditions rubrics, teacher self-assessment tools, and planning guides to help educators build, mobilize, and sustain deep learning in schools and districts. Learn about, improve, and expand your world of learning. Put the joy back into learning for students and adults alike. Dive into deep learning to create learning experiences that give purpose, unleash student potential, and transform not only learning, but life itself.
Author: James C. Scott Publisher: Yale University Press ISBN: 0300156529 Category : Social Science Languages : en Pages : 465
Book Description
From the acclaimed author and scholar James C. Scott, the compelling tale of Asian peoples who until recently have stemmed the vast tide of state-making to live at arm’s length from any organized state society For two thousand years the disparate groups that now reside in Zomia (a mountainous region the size of Europe that consists of portions of seven Asian countries) have fled the projects of the organized state societies that surround them—slavery, conscription, taxes, corvée labor, epidemics, and warfare. This book, essentially an “anarchist history,” is the first-ever examination of the huge literature on state-making whose author evaluates why people would deliberately and reactively remain stateless. Among the strategies employed by the people of Zomia to remain stateless are physical dispersion in rugged terrain; agricultural practices that enhance mobility; pliable ethnic identities; devotion to prophetic, millenarian leaders; and maintenance of a largely oral culture that allows them to reinvent their histories and genealogies as they move between and around states. In accessible language, James Scott, recognized worldwide as an eminent authority in Southeast Asian, peasant, and agrarian studies, tells the story of the peoples of Zomia and their unlikely odyssey in search of self-determination. He redefines our views on Asian politics, history, demographics, and even our fundamental ideas about what constitutes civilization, and challenges us with a radically different approach to history that presents events from the perspective of stateless peoples and redefines state-making as a form of “internal colonialism.” This new perspective requires a radical reevaluation of the civilizational narratives of the lowland states. Scott’s work on Zomia represents a new way to think of area studies that will be applicable to other runaway, fugitive, and marooned communities, be they Gypsies, Cossacks, tribes fleeing slave raiders, Marsh Arabs, or San-Bushmen.
Author: William L. William L. Hamilton Publisher: Springer Nature ISBN: 3031015886 Category : Computers Languages : en Pages : 141
Book Description
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
Author: Tor Lattimore Publisher: Cambridge University Press ISBN: 1108486827 Category : Business & Economics Languages : en Pages : 537
Book Description
A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.
Author: Hao Yuan
Author: Jing-Sheng J. Song
Author: Xi Chen
Author: Justin Sirignano
Author: Steven Nahmias
Author: Joanne Quinn
Author: Sean Meyn
Author: James C. Scott
Author: William L. William L. Hamilton
Author: Tor Lattimore