Cost-Based Filtering Techniques for Stochastic Inventory Control Under Service Level Constraints

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Date

2009

Journal Title

Journal ISSN

Volume Title

Publisher

Springer

Open Access Color

BRONZE

Green Open Access

No

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

Yes
Impulse
Top 10%
Influence
Top 10%
Popularity
Average

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Journal Issue

Abstract

This paper(1) considers a single product and a single stocking location production/inventory control problem given a non-stationary stochastic demand. Under a widely-used control policy for this type of inventory system, the objective is to find the optimal number of replenishments, their timings and their respective order-up-to-levels that meet customer demands to a required service level. We extend a known CP approach for this problem using three cost-based filtering methods. Our approach can solve to optimality instances of realistic size much more efficiently than previous approaches, often with no search effort at all.

Description

Keywords

Inventory control, Non-stationary (R, S) policy, Stochastic demand, Cost-based filtering, Dynamic programming relaxation, Lot-Sizing Problem, Demand, Algorithms, Systems, lot-sizing problem, Cost-based filtering, Non-stationary (R, S) policy, systems, demand, algorithms, Stochastic demand, Dynamic programming relaxation, Inventory control, non-stationary \((R,S)\) policy, dynamic programming relaxation, Inventory, storage, reservoirs, cost-based filtering, Dynamic programming, Optimal stochastic control, stochastic demand, inventory control

Fields of Science

0211 other engineering and technologies, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences

Citation

WoS Q

Q3

Scopus Q

Q3
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OpenCitations Citation Count
13

Source

Constraınts

Volume

14

Issue

2

Start Page

137

End Page

176
PlumX Metrics
Citations

CrossRef : 11

Scopus : 10

Captures

Mendeley Readers : 11

SCOPUS™ Citations

10

checked on Mar 17, 2026

Web of Science™ Citations

8

checked on Mar 17, 2026

Page Views

3

checked on Mar 17, 2026

Downloads

13

checked on Mar 17, 2026

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4.4632

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