Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Risk analysis is crucial in stochastic supply chain models. Over the past few years, the pace has quickened for  research attempting to explore risk analysis issues in supply chain management problems, while the majority of recent papers focus on conceptual framework or computational numerical analysis.  Pioneered by Nobel laureate Markowitz in the 1950s, the mean-risk (MR) formulation became a fundamental theory for risk management in finance. Despite the significance and popularity of MR-related approaches in finance, their applications in studying multi-echelon supply chain management problems have only been seriously explored in recent years. While the MR approach has already been shown to be useful in conducting risk analysis in stochastic supply chain models, there is no comprehensive reference source that provides the state-of-the-art findings on this important model for supply chain management. Thus it is significant to have a book that reviews and extends the MR related works for supply chain risk analysis.  This book is organized into five chapters. Chapter 1 introduces the topic, offers a timely review of various related areas, and explains why the MR approach is important for conducting supply chain risk analysis. Chapter 2 examines the single period inventory model with the mean-variance and mean-semi-deviation approaches. Extensive discussions on the efficient frontiers are also reported. Chapter 3 explores the infinite horizon multi-period inventory model with a mean-variance approach. Chapter 4 investigates the supply chain coordination problem with a versatile target sales rebate contract and a risk averse retailer possessing the mean-variance optimization objective. Chapter 5 concludes the book and discusses various promising future research directions and extensions. Every chapter can be taken as a self-contained article, and the notation within each chapter is consistently employed.

Business logistics -- Management. --- Business logistics -- Risk management. --- Business. --- Economics. --- Business logistics --- Management --- Business & Economics --- Management Theory --- Management Styles & Communication --- Risk management --- Risk management. --- Management. --- Supply chain management --- Production management. --- Operations research. --- Decision making. --- Management science. --- Business and Management. --- Operation Research/Decision Theory. --- Operations Research, Management Science. --- Operations Management. --- Industrial management --- Logistics --- Operations Research/Decision Theory. --- Manufacturing management --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Quantitative business analysis --- Problem solving --- Operations research --- Statistical decision --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management decisions --- Choice (Psychology) --- Decision making

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This work encapsulates the essential developments in this field into a single resource, as well as to set an agenda for further development in the field. This brief focuses on the demand flexibility in supply chains with fragmented results distributed throughout the literature. These results have strong implications for managing real-world complex operations planning problems. This book exploits dimensions of demand flexibility in supply chains and characterizes the best fit between demand properties and operations capabilities and constraints. The origins and seminal works are traced in integrated demand and operations planning and an in-depth documentation is provided for the current state of the art. Systems with inherent costs and constraints that must respond to some set of demands at a minimum cost are examined.  Crucial unanswered questions are explored and the high-value research directions  are highlighted for both practice and for the development of new and interesting optimization models and algorithms.

Business logistics -- Management. --- Engineering economy. --- Mathematical optimization. --- Operations research. --- Business logistics --- Operations research --- Civil & Environmental Engineering --- Management --- Business & Economics --- Engineering & Applied Sciences --- Operations Research --- Management Styles & Communication --- Supply and demand. --- Business logistics. --- Supply chain management --- Demand and supply --- Industrial production --- Law of supply and demand --- Mathematics. --- Production management. --- Management science. --- Engineering economics. --- Operations Research, Management Science. --- Engineering Economics, Organization, Logistics, Marketing. --- Optimization. --- Operations Management. --- Economy, Engineering --- Engineering economics --- Industrial engineering --- Quantitative business analysis --- Problem solving --- Statistical decision --- Operational analysis --- Operational research --- Management science --- Research --- System theory --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Simulation methods --- System analysis --- Manufacturing management --- Industrial management --- Math --- Science --- Logistics --- Economics --- Competition --- Exchange --- Overproduction --- Prices --- Value