Design for postponement: A comprehensive characterization of its benefits under unknown demand distributions

Operations Research

Volumn 49, Issue 4, 2001, Pages 578-598

  Aviv, Yossi ^b   Federgruen, Awi ^b  

^a WASHINGTON UNIVERSITY IN ST LOUIS   (United States)

^b NONE

Author keywords

[No Author keywords available]

Indexed keywords

INVENTORY CONTROL; THEOREM PROVING;

DEMAND DISTRIBUTIONS;

OPERATIONS RESEARCH;

EID: 0034750213     PISSN: 0030364X     EISSN: None     Source Type: Journal    
DOI: 10.1287/opre.49.4.578.11229     Document Type: Article

References (56)

1. Marketing efficiency and the principle of postponement
2. Capacitated multi-item inventory systems with random and seasonally fluctuating demands: Implications for postponement strategies
3. Bayes solution to dynamic inventory models under unknown demand distribution
4. A comparison of the optimal ordering levels of Bayesian and non-bayesian inventory models
5. The inventory problem: II. Case of unknown distributions of demand
6. Centralized ordering policies in a multiwarehouse system with leadtimes and random demands
7. The power approximation for computing (s, S) inventory policies
8. Optimal centralized ordering policies in multi-echelon inventory systems with correlated demands
9. Recent advances in production and distribution management
10. Approximations of dynamic, multilocation production and inventory problems
11. Allocation policies and cost approximations for multilocation inventory systems
12. Computational issues in an infinite horizon multi-echelon inventory model
13. Reducing the cost of demand uncertainty through accurate response to early sales
14. Accurate response: The key to profiting from quick response
15. Making supply meet demand in an uncertain world
16. Discrete optimization via marginal analysis
17. The distribution free newsboy problem: Review and extensions
18. On postponement strategies for product families with multiple points of differentiation
19. A two-echelon allocation model and the value of information under correlated forecasts and demands
20. Modeling the evolution of demand forecasts with applications to safety stock analysis in production/distribution systems
21. The dynamic inventory model with unknown demand distribution
22. Quick response in manufacturer-retailer channels
23. Stock allocation in a two echelon distribution system or "what to do until your ship comes in"
24. Optimality of myopic inventory policies for certain dependent demand processes
25. Analysis of a two-echelon inventory control system with complete redistribution
26. Modification of demand distributions on the basis of aggregate information
27. Dynamic inventory policy with varying stochastic demands
28. Design for supply chain management: Concepts and examples
29. Effective management Of inventory and service through product and process redesign
30. Designing products and processes for postponement
31. Hewlett-Packard gains control of inventory and service through design for localization
32. Modeling the costs and benefits of delayed product differentiation
33. Myopic policies for some inventory models with uncertain demand
34. Scarf's state reduction method, flexibility, and a dependent demand inventory model
35. Supply chain strategies at Sun Microsystems
36. A min-max solution of an inventory problem
37. Bayes solutions of the statistical inventory problem
38. Some remarks on Bayes solutions to the inventory problem
39. Model for assessing the value of warehouse risk-pooling: Risk pooling over outside-supplier leadtimes
40. Optimality of (s, S) policies in inventory models with Markovian demand
41. Inventory control in a fluctuating demand environment
42. Competing on capabilities: The new rules of corporate strategy
43. Minimizing a submodular function on a lattice
44. Optimal policy for a multi-product, dynamic non-stationary inventory problem
45. GM expands plan to speed cars to buyers
46. Simple ranking methods for allocation of one resource
47. Exact approximate cost functions for product aggregates