Real problems are formulated into tractable mathematical models, which allow for an analysis of various approaches. Attention is focused on solutions. Provides a unified treatment of the models discussed , presents a critique of the existing results, and points out potential research directions.
The focus of the work is twofold. First, it provides an introduction into fundamental structural and behavioral aspects of periodic review inventory systems. Second, it includes a comprehensive study on analytical and optimization aspects of a specific class of those systems. For the latter purpose, general solution methods for problems of inventory management in discrete time are described and developed along with highly specialized methods to solve very specific problems related to the model variants examined. The work is thus addressed to students and practitioners who seek a deeper understanding of managing inventories in discrete time as well as to software developers who require implementation aids on specific problems of inventory management.
Companies with high-performing supply chains enjoy essential competitive ad- vantages. However, supply chain management faces an environment of rising risk that endangers these competitive advantages. One of the reasons is to outsource parts of their business. This bears the risk of significantly increased lead times and lead time variability. It is the impact of lead time variability on inventory management that is the central aspect of this book. It describes a mathematical model for dual sourcing with two reorder points, shows the deviation between stochastic and deterministic calculations in a sensitivity analysis, and investigates different relaxations of a traditional dual-sourcing policy.
Quick Response (QR) policy is a market-driven business strategy in which supply chain members work together to react quickly to volatile market demand. Nowadays, with advances in information technologies (such as RFID and ERP systems), new challenges and opportunities arise for the application of QR. This handbook explores QR extensively with a view to discovering innovative QR measures that can help tackle the observed and emerging challenges. The book is organized into four parts, which include chapters on analytical modeling and analyses, information technologies, cases, reviews, and applications. This handbook provides new analytical and empirical results with valuable insights, which will not only help supply chain agents to better understand the latest applications of QR in business, but also help practitioners and researchers to know how to improve the effectiveness of QR using innovative methods.
This edited volume contains 16 research articles. It presents recent and pressing issues in stochastic processes, control theory, differential games, optimization, and their applications in finance, manufacturing, queueing networks, and climate control. One of the salient features is that the book is highly multi-disciplinary. The book is dedicated to Professor Suresh Sethi on the occasion of his 60th birthday, in view of his distinguished career.
Fierce competition in today's global market provides a powerful motivation for developing ever more sophisticated logistics systems. This book, written for the logistics manager and researcher, presents a survey of the modern theory and application of logistics. The goal of the book is to present the state-of-the-art in the science of logistics management. As a result, the authors have written a timely and authoritative survey of this field that many practitioners and researchers will find makes an invaluable companion to their work.
A number of methodologies have been employed to provide decision making solutions globalized markets. Hidden Markov Models in Finance offers the first systematic application of these methods to specialized financial problems: option pricing, credit risk modeling, volatility estimation and more. The book provides tools for sorting through turbulence, volatility, emotion, chaotic events – the random "noise" of financial markets – to analyze core components.
For first courses in operations research, operations management Optimization in Operations Research, Second Edition covers a broad range of optimization techniques, including linear programming, network flows, integer/combinational optimization, and nonlinear programming. This dynamic text emphasizes the importance of modeling and problem formulation andhow to apply algorithms to real-world problems to arrive at optimal solutions. Use a program that presents a better teaching and learning experience-for you and your students. Prepare students for real-world problems: Students learn how to apply algorithms to problems that get them ready for their field. Use strong pedagogy tools to teach: Key concepts are easy to follow with the text's clear and continually reinforced learning path. Enjoy the text's flexibility: The text features varying amounts of coverage, so that instructors can choose how in-depth they want to go into different topics.