Foundations of Stochastic Inventory Theory

By Evan L. Porteus. 2002

669 citations recorded by the source corpus.

A loom mechanism and method which delays the harness crossing and provides tighter, more uniform beat-up during the weaving process.

Subfields: Artificial Intelligence

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Citations in the corpus

Optimality Conditions for Inventory Control (2016, background): “The reader may find coverage of these topics in books on MDPs (Bäuerle and Rieder [3], Bertsekas and Shreve [12], Dynkin and Yushkevich [22], Feinberg and Shwartz [29], Heyman and Sobel [42], Hernández-Lerma [38], Hernández-Lerma and Lasserre [40, 41], Puterman [47], Sennott [54]) and on inventory m”
Joint inventory and pricing decisions with reference effects (2014, methodology): “D is convex and hence concavity of Wt(x, r ) follows directly from Porteus (2002).”
Supply chain finance: Optimal introduction and adoption decisions (2016, background): “Many important distributions have the IFR property (e.g., normal, gamma and uniform) and the assumption of an IFR function is widely used in many operations and supply chain management contexts (Cachon 2003, Lariviere 2006, Porteus 2002).”
RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning (2014, background): “It is important that the error is with respect to the optimal value function which can have special structural properties, such as convexity in inventory management problems (Porteus, 2002).”
Dynamic inventory management with cash flow constraints (2008, background): “The majority of the current literature on inventory management ignores financial status of a firm and assumes that the firm is able to implement any replenishment and ordering decisions, see, [2, 14, 15, 19].”
Sharing Demand Information in Competing Supply Chains with Production Diseconomies (2011, methodology): “Such an assumption is commonly used in the inventory (Porteus 2002) and queuing (e.”
How Inventory Is (Should Be) Financed: Trade Credit in Supply Chains with Demand Uncertainty and Costs of Financial Distress (2013, positive): “Dealing with a problem similar to that in Lariviere and Porteus (2001), we also assume ξ has an increasing generalized failure rate distribution (IGFR).”
Robust and Data-Driven Optimization: Modern Decision-Making Under Uncertainty (2006, background): “…meet the demand w t , and order the missing items, i.e., w t − x t , otherwise, which is known in inventory management as a (S,S) policy with basestock level w t at time t. (The basestock level quantifies the amount of inventory on hand or on order at a given time period, see, e.g., Porteus [35].)”
Information Transmission and the Bullwhip Effect: An Empirical Investigation (2012, positive): “…order quantities to normal random variables, the optimal production capacity and mean inventory, with respect to the stock-up-to variables, are (see Porteus 2002, p. 13) zzw i l = −1 ¯ c ¯ c + s Varo t w i l and mmw i l = −1 b b + h Vari t w i l (4) Using (4), we recast the objective to depend…”
Optimal Threshold Control for Energy Arbitrage with Degradable Battery Storage (2015, background): “On the other hand, the optimality of threshold policies has been studied widely in the inventory management literature [Porteus, 2002].”
Bounded Rationality in Newsvendor Models (2008, background): “First, for the basic newsvendor model, it is well known that the optimal solution is characterized by the critical fractile; Porteus (2002).”
Customer‐Base Concentration and Inventory Efficiencies: Evidence from the Manufacturing Sector (2016, background): “In turn, enhanced demand forecasting leads to a reduction of inventory investment because the optimal buffer size of the safety stock is an increasing function of demand uncertainty (e.g., Porteus 2002, Zipkin 2000).”
Optimal Stopping With Multiple Priors (2009, background): “Even if we invoke Savage’s theory of subjective probability, there is by now sufficient evidence that rational agents as well as 1see Dixit and Pindyck (1994), e.g. 2see Duffie (1992), e.g. 3see Porteus (1990), e.g. 4see Wald (1947). real persons use different approaches.”
Inventory Record Inaccuracy, Double Marginalization, and RFID Adoption (2007, background): “Assuming full inventory transparency under RFID, the supply chain in this scenario (subscript 2) faces the standard newsvendor problem (cf. Porteus 2002) and expected proﬁts are Proposition 2 provides the optimal order quantity and expected proﬁts for the integrated supply chain under RFID…”
A simulation based optimization approach to supply chain management under demand uncertainty (2004, background): “An extensive discussion of the foundational work can be found in Porteus (2002) and Hopp and Spearman (2000).”