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Decomposition Approach for Simulation-Based Optimization of Inventory Management. / Yuskov, Alexander; Kulachenko, Igor; Melnikov, Andrey et al.

Communications in Computer and Information Science. Springer Science and Business Media Deutschland GmbH, 2023. p. 259-273 (Communications in Computer and Information Science; Vol. 1881 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Yuskov, A, Kulachenko, I, Melnikov, A & Kochetov, Y 2023, Decomposition Approach for Simulation-Based Optimization of Inventory Management. in Communications in Computer and Information Science. Communications in Computer and Information Science, vol. 1881 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 259-273. https://doi.org/10.1007/978-3-031-43257-6_20

APA

Yuskov, A., Kulachenko, I., Melnikov, A., & Kochetov, Y. (2023). Decomposition Approach for Simulation-Based Optimization of Inventory Management. In Communications in Computer and Information Science (pp. 259-273). (Communications in Computer and Information Science; Vol. 1881 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-43257-6_20

Vancouver

Yuskov A, Kulachenko I, Melnikov A, Kochetov Y. Decomposition Approach for Simulation-Based Optimization of Inventory Management. In Communications in Computer and Information Science. Springer Science and Business Media Deutschland GmbH. 2023. p. 259-273. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-43257-6_20

Author

Yuskov, Alexander ; Kulachenko, Igor ; Melnikov, Andrey et al. / Decomposition Approach for Simulation-Based Optimization of Inventory Management. Communications in Computer and Information Science. Springer Science and Business Media Deutschland GmbH, 2023. pp. 259-273 (Communications in Computer and Information Science).

BibTeX

@inproceedings{7489931a201b40e389af29f33426bc73,
title = "Decomposition Approach for Simulation-Based Optimization of Inventory Management",
abstract = "We consider a two-echelon inventory management problem, where customers{\textquoteright} requests for spare parts of different types must be fulfilled within a given service level threshold. The supply system is composed of multiple warehouses in the first echelon, where the customers{\textquoteright} requests are processed, and a single second-echelon warehouse, replenishing stocks of the first-echelon warehouses. Replenishment requests of warehouses are invoked according to inventory policies, which are characterized by one or two numerical parameters and are individual for each warehouse and each spare part type. The goal is to minimize the total storage cost for all warehouses at both echelons. System operation is simulated within a black-box function that computes the request satisfaction rate and inventory holding costs depending on the policy parameters. In the work, we propose a decomposition approach to adjust these parameters for an industrial-sized supply system. Computational experiments for up to 1,000 types of items and 100 warehouses are discussed.",
keywords = "Grey-box optimization, Local search, Multiple-choice knapsack problem",
author = "Alexander Yuskov and Igor Kulachenko and Andrey Melnikov and Yury Kochetov",
note = "The study was carried out within the framework of the state contract of the Sobolev Institute of Mathematics (project FWNF–2022–0019).",
year = "2023",
doi = "10.1007/978-3-031-43257-6_20",
language = "English",
isbn = "9783031432569",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "259--273",
booktitle = "Communications in Computer and Information Science",
address = "Germany",

}

RIS

TY - GEN

T1 - Decomposition Approach for Simulation-Based Optimization of Inventory Management

AU - Yuskov, Alexander

AU - Kulachenko, Igor

AU - Melnikov, Andrey

AU - Kochetov, Yury

N1 - The study was carried out within the framework of the state contract of the Sobolev Institute of Mathematics (project FWNF–2022–0019).

PY - 2023

Y1 - 2023

N2 - We consider a two-echelon inventory management problem, where customers’ requests for spare parts of different types must be fulfilled within a given service level threshold. The supply system is composed of multiple warehouses in the first echelon, where the customers’ requests are processed, and a single second-echelon warehouse, replenishing stocks of the first-echelon warehouses. Replenishment requests of warehouses are invoked according to inventory policies, which are characterized by one or two numerical parameters and are individual for each warehouse and each spare part type. The goal is to minimize the total storage cost for all warehouses at both echelons. System operation is simulated within a black-box function that computes the request satisfaction rate and inventory holding costs depending on the policy parameters. In the work, we propose a decomposition approach to adjust these parameters for an industrial-sized supply system. Computational experiments for up to 1,000 types of items and 100 warehouses are discussed.

AB - We consider a two-echelon inventory management problem, where customers’ requests for spare parts of different types must be fulfilled within a given service level threshold. The supply system is composed of multiple warehouses in the first echelon, where the customers’ requests are processed, and a single second-echelon warehouse, replenishing stocks of the first-echelon warehouses. Replenishment requests of warehouses are invoked according to inventory policies, which are characterized by one or two numerical parameters and are individual for each warehouse and each spare part type. The goal is to minimize the total storage cost for all warehouses at both echelons. System operation is simulated within a black-box function that computes the request satisfaction rate and inventory holding costs depending on the policy parameters. In the work, we propose a decomposition approach to adjust these parameters for an industrial-sized supply system. Computational experiments for up to 1,000 types of items and 100 warehouses are discussed.

KW - Grey-box optimization

KW - Local search

KW - Multiple-choice knapsack problem

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85174627019&origin=inward&txGid=eac71dede38777413670618375b6f74d

UR - https://www.mendeley.com/catalogue/d7f8045d-7394-373c-81b9-d927009c3abb/

U2 - 10.1007/978-3-031-43257-6_20

DO - 10.1007/978-3-031-43257-6_20

M3 - Conference contribution

SN - 9783031432569

T3 - Communications in Computer and Information Science

SP - 259

EP - 273

BT - Communications in Computer and Information Science

PB - Springer Science and Business Media Deutschland GmbH

ER -

ID: 59183369