And Then There Were None

References

• Arrow K. J., Harris T., Marschak J. Optimal inventory policy. Econometrica (1951) 19:250–272Crossref, Google Scholar
• Arrow K. J., Karlin S., Scarf H.Studies in the Mathematical Theory of Inventory and Production (1958) (Stanford University Press, Stanford, CA) Google Scholar
• Bellman R.Dynamic Programming (1957) (Princeton University Press, Princeton, NJ) Google Scholar
• Bellman R., Glicksberg I., Gross O. On the optimal inventory equation. Management Sci. (1955) 2:83–104Link, Google Scholar
• Blazer D. Testing the cost effectiveness of an inventory filtering rule using empirical data. (1983) (University of North Carolina at Chapel Hill, Chapel Hill, NC) . Ph.D. thesis School of Business AdministrationGoogle Scholar
• Bowman E. H. Production scheduling by the transportation method of linear programming. Oper. Res. (1956) 100–103Link, Google Scholar
• Brown R. G.Statistical Forecasting for Inventory Control (1959) (McGraw Hill, New York) Google Scholar
• Clark A. J., Scarf H. E. Optimal policies for a multiechelon inventory problem. Management Sci. (1960) 6:475–490Link, Google Scholar
• Dvoretzky A., Kiefer J., Wolfowitz J. The inventory problem. I: Case of known distributions of demand. Econometrica (1952a) 20:187–222Crossref, Google Scholar
• Dvoretzky A., Kiefer J., Wolfowitz J. The inventory problem. II: Case of unknown distributions of demand. Econometrica (1952b) 20:450–466Crossref, Google Scholar
• Dvoretzky A., Kiefer J., Wolfowitz J. On the optimal character of (s, S) policy in inventory theory. Econometrica (1953) 20:586–596Crossref, Google Scholar
• Ehrhardt R. The power approximation for computing (s, S) inventory policies. Management Sci. (1979) 25:777–786Link, Google Scholar
• Ehrhardt R., Mosier C. A revision of the power approximation for computing (s, S) inventory policies. Management Sci. (1979) 30:618–622Link, Google Scholar
• Ehrhardt R., Wagner H. M., Greenberg H. J., Murphy F. H., Shaw S. H. Inventory models and practice. Advanced Techniques in the Practice of Operations Research (1982) (North-Holland, New York) 251–332Google Scholar
• Ehrhardt R., Schulz C. R., Wagner H. M., Schwarz L. (s, S)Policies for a Wholesale Inventory System. Multi-Level Production/Inventory Systems: Theory and Practice (1980) (North-Holland, New York) 141–161Google Scholar
• Estey A. S., Kaufman R. Multi-item inventory system policies using statistical estimates: Negative binomial demand. (1975) . Working paper, Yale University, New Haven, CTGoogle Scholar
• Forrester J. W. Industrial dynamics—A major breakthough for decisionmakers. Understanding the forces causing industrial fluctions growth, and decline. Harvard Bus. Rev. (1958) 36(July–August):37–66Google Scholar
• Forrester J. W.Industrial Dynamics (1961) (The MIT Press, Cambridge, MA) Google Scholar
• Hayes R. H. Statistical estimation problems in inventory control. Management Sci. (1969) 15:686–701Link, Google Scholar
• Hayes R. H. Efficiency of simple order statistic estimates when losses are piecewise linear. J. Amer. Statist. Assoc. (1971) 66:127–135Crossref, Google Scholar
• Holt C. C., Modigliani F., Muth J. F. Derivation of a linear decision rule for production and employment. Management Sci. (1956) 2:159–177Link, Google Scholar
• Holt C. C., Modigliani F., Muth J. F., Simon H. A.Planning, Production, Inventories, and Work Force (1960) (Prentice Hall, Englewood Cliffs, NJ) Google Scholar
• Jacobs R. A., Wagner H. M. Reducing inventory system costs by using robust demand estimators. Management Sci. (1989a) 35:771–787Link, Google Scholar
• Jacobs R. A., Wagner H. M. Lowering inventory system costs by using regression-derived estimators of demand variability. Decision Sci. (1989b) 20:558–574Crossref, Google Scholar
• Johnson S. M. Sequential production planning over time at minimum cost. Management Sci. (1957) 3:435–437Link, Google Scholar
• Karlin S. Dynamic inventory policy with varying stochastic demands. Management Sci. (1960) 6:231–258Link, Google Scholar
• Kaufman R. L. (s, S) inventory policies in a nonstationary demand environment. (1977) . Working paper, University of North Carolina at Chapel Hill, Chapel Hill, NCGoogle Scholar
• Kaufman R. L., Klincewicz J. Multi-item inventory system policies using statistical estimates: Sporadic demand. (1976) . Working paper, Yale University, New Haven, CTGoogle Scholar
• Klincewicz J. G. Biased variance estimators for statistical inventory policies. (1976a) (Yale University, New Haven, CT) Google Scholar
• Klincewicz J. G. Inventory control using statistical estimates: The power approximation and sporadic demands. (1976b) (Yale University, New Haven, CT) Google Scholar
• Klincewicz J. G. The power approximation: Control of multi-item inventory systems with constant standard-deviation-to-mean ratio for demand. (1976c) (Yale University, New Haven, CT) Crossref, Google Scholar
• Laderman J., Littauer S. B., Weiss L. The inventory problem. J. Amer. Statist. Assoc. (1953) 48:717–732Crossref, Google Scholar
• MacCormick A. Predicting the cost performance of inventory control systems by retrospective simulation. Naval Res. Logist. Quart. (1978) 25:605–620Crossref, Google Scholar
• MacCormick A., Estey A.S., Kaufman R. L. Inventory control with statistical demand information. (1977) (Working paper, University of North Carolina at Chapel Hill, Chapel Hill, NC)Google Scholar
• Manne A. S. Programming of economic lot sizes. Management Sci. (1958) 4:115–135Link, Google Scholar
• Modigliani F., Hohn F. Production planning over time and the nature of the expectation and planning horizon. Econometrica (1955) 23:46–66Crossref, Google Scholar
• Morse P.Queues Inventories, and Maintenance (1958) (John Wiley & Sons, New York) Crossref, Google Scholar
• Peterson D. K. The (s, S) inventory model under low demand. (1987) (University of North Carolina at Chapel Hill, Chapel Hill, NC) . Ph.D. thesis, School of Business AdministrationGoogle Scholar
• Roberts D. M. Approximations to optimal policies in a dynamic inventory model. Studies in Applied Probability and Management Science (1962) (Stanford University Press, Stanford, CA) 196–202Google Scholar
• Scarf H. Bayes solutions of the statistical inventory problem. Ann. Math. Statist (1959) 30:490–508Crossref, Google Scholar
• Scarf H., Arrow K., Karlin S., Suppes P. The optimality of (S, s) policies in the dynamic inventory problem. Mathematical Methods in the Social Sciences (1960) (Stanford University Press, Stanford, CA) Google Scholar
• Schulz C. R. Wholesale warehouse inventory control with statistical demand information. (1980) (University of North Carolina at Chapel Hill, Chapel Hill, NC) . Ph.D. thesis, Operations Research and Systems AnalysisGoogle Scholar
• Schulz C. R., Ehrhardt R., MacCormick A. Forecasting operating characteristics of (s,S) inventory systems. (1977) . Working paper, School of Business Administration. University of North Carolina at Chapel Hill, Chapel Hill, NCGoogle Scholar
• Silver E. A., Pyke D. F., Peterson R.Inventory Management and Production Planning and Scheduling (1998) 3rd ed.(John Wiley & Sons, New York) Google Scholar
• Simon H. A. On the application of servomechanism theory in the study of production control. Econometrica (1952) 20:247–268Crossref, Google Scholar
• Simon H. A. Dynamic programming under uncertainty with a quadratic criterion function. Econometrica (1956) 24:74–81Crossref, Google Scholar
• Veinott A., Scarf H., Gilford D., Shelly M. Optimal stockage policies with nonstationary stochastic demands. Multistage Inventory Models and Techniques (1963) (Stanford University Press, Stanford, CA) . Chapter 4Google Scholar
• Veinott A. Optimal policy for a multi-product, dynamic, nonstationary inventory problem. Management Sci. (1965) 12:206–222Link, Google Scholar
• Veinott A. The status of mathematical inventory theory. Management Sci. (1966) 12:745–777Link, Google Scholar
• Veinott A., Wagner H. M. Computing optimal (s,S) inventory policies. Management Sci. (1965) 11:525–552Link, Google Scholar
• Wagner H. M.Statistical Management of Inventory Systems (1962) (John Wiley & Sons, New York) Google Scholar
• Wagner H. M.Principles of Operations Research (1969) (Prentice Hall, Englewood Cliffs, NJ) Google Scholar
• Wagner H. M., Whitin T. M. Dynamic problems in the theory of the firm. The Theory of Inventory Management (1957) (Princeton University Press, Princeton, NJ) 299–327Google Scholar
• Wagner H. M., Whitin T. M. Dynamic version of the economic lot size model. Management Sci. (1958) 5:89–96Link, Google Scholar