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Technical note —Linear Inflation Rules for the Random Yield Problem: Analysis and Computations

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Supply Chain and Inventory Management Management and Optimization Techniques Advanced Manufacturing and Logistics Optimization

Abstract

In this paper, we propose a simple heuristic approach for the inventory control problem with stochastic demand and multiplicative random yield. Our heuristic tries to find the best candidate within a class of policies that are referred to in the literature as the linear inflation rule (LIR) policies. Our approach is computationally fast, easy to implement, and intuitive to understand. Moreover, we find that in a significant number of instances our heuristic performs better than several other well-known heuristics that are available in the literature.

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References

2000Foundations of Inventory Management 1995Lot Sizing with Random Yields: A Review 1990The Structure of Periodic Review Policies in the Presence of Random Yield 1995Sensitivity Analysis for Base-Stock Levels in Multiechelon Production-Inventory Systems 1999Myopic Heuristics for the Random Yield Problem 2004Lost-Sales Problems with Stochastic Lead Times: Convexity Results for Base-Stock Policies 2010An inventory model with random replenishment quantities.

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2019Dynamic Volunteer Staffing in Multicrop Gleaning Operations 2012Managing a Remanufacturing System with Random Yield: Properties, Observations, and Heuristics 2015Exact and heuristic linear-inflation policies for an inventory model with random yield and arbitrary lead times 2016Dual Sourcing Under Random Supply Capacities: The Role of the Slow Supplier 2014Infinite Horizon Strategies for Replenishment Systems with a General Pool of Suppliers 2020Technical Note—Constant-Order Policies for Lost-Sales Inventory Models with Random Supply Functions: Asymptotics and Heuristic

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