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Achieving High Individual Service Levels Without Safety Stock? Optimal Rationing Policy of Pooled Resources

Published: 01 January 2023 Publication History

Abstract

In “Achieving High Individual Service-Levels without Safety Stock? Optimal Rationing Policy of Pooled Resources,” Jiang, Wang, and Zhang analyze a resource rationing problem with service level constraints. They present a general framework to study the two-stage problem when customers require individual and possibly different service levels: (1) the capacity level of pooled resources in anticipation of random demand of multiple customers and (2) how the capacity should be allocated to fulfill customer demands after demand realization. The modeling framework generalizes and unifies many existing models in the literature and includes second-stage allocation costs. The authors propose a simple randomized rationing policy for any fixed feasible capacity level and show the optimality of this policy for very general service level constraints, including type I and type II constraints and beyond. They also discuss the optimality of index policies.

Abstract

Resource pooling is a fundamental concept that has many applications in operations management for reducing and hedging uncertainty. An important problem in resource pooling is to decide (1) the capacity level of pooled resources in anticipation of random demand of multiple customers and (2) how the capacity should be allocated to fulfill customer demands after demand realization. In this paper, we present a general framework to study this two-stage problem when customers require individual and possibly different service levels. Our modeling framework generalizes and unifies many existing models in the literature and includes second-stage allocation costs. We propose a simple randomized rationing policy for any fixed feasible capacity level. Our main result is the optimality of this policy for very general service level constraints, including type I and type II constraints and beyond. The result follows from a semi-infinite linear programming formulation of the problem and its dual. As a corollary, we also prove the optimality of index policies for a large class of problems when the set of feasible fulfilled demands is a polymatroid.
Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2022.2386.

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  • (2024)Multiobjective Stochastic OptimizationManufacturing & Service Operations Management10.1287/msom.2020.024726:2(500-518)Online publication date: 1-Mar-2024

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              Published In

              cover image Operations Research
              Operations Research  Volume 71, Issue 1
              January-February 2023
              400 pages
              ISSN:0030-364X
              DOI:10.1287/opre.2023.71.issue-1
              Issue’s Table of Contents

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              INFORMS

              Linthicum, MD, United States

              Publication History

              Published: 01 January 2023
              Accepted: 21 August 2022
              Received: 28 January 2021

              Author Tag

              1. Operations and Supply Chains

              Author Tags

              1. inventory management
              2. two-stage stochastic program
              3. service level constraints
              4. online gradient descent

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              • (2024)Multiobjective Stochastic OptimizationManufacturing & Service Operations Management10.1287/msom.2020.024726:2(500-518)Online publication date: 1-Mar-2024

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