Demand Flexibility in Supply Chain Planning [electronic resource] / by Joseph Geunes.
Contributor(s): SpringerLink (Online service)Material type: TextSeries: SpringerBriefs in Optimization: Publisher: New York, NY : Springer New York : Imprint: Springer, 2012Description: XIII, 90 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781441993472Subject(s): Mathematics | Production management | Mathematical optimization | Operations research | Management science | Engineering economics | Engineering economy | Mathematics | Operations Research, Management Science | Engineering Economics, Organization, Logistics, Marketing | Optimization | Operations ManagementAdditional physical formats: Printed edition:: No titleDDC classification: 519.6 LOC classification: QA402-402.37T57.6-57.97Online resources: Click here to access online
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1. Scope of Problem Coverage and Introduction -- 2. Production and Inventory Planning Models with Demand Shaping -- 3. EOQ-Type Models with Demand Selection -- 4. Single-Period Stochastic Inventory Planning with Demand Selection -- 5. Dynamic Lot Sizing with Demand Selection and the Pricing Analog -- 6. Dynamic Lot Sizing with Market Selection -- 7. Assignment and Location Problems in Supply Chains -- 8. Branch and Price Decomposition for Assignment and Location Problems -- 9. Research Challenges in Supply Chain Planning with Flexible Demand.
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.