A1 Journal article (refereed)
Flexible data driven inventory management with interactive multiobjective lot size optimization (2023)

Heikkinen, R., Sipilä, J., Ojalehto, V., & Miettinen, K. (2023). Flexible data driven inventory management with interactive multiobjective lot size optimization. International Journal of Logistics Systems and Management, 46(2), 206-235. https://doi.org/10.1504/IJLSM.2023.134404

JYU authors or editors

Publication details

All authors or editors: Heikkinen, Risto; Sipilä, Juha; Ojalehto, Vesa; Miettinen, Kaisa

Journal or series: International Journal of Logistics Systems and Management

ISSN: 1742-7967

eISSN: 1742-7975

Publication year: 2023

Publication date: 20/10/2023

Volume: 46

Issue number: 2

Pages range: 206-235

Publisher: Inderscience Publishers

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1504/IJLSM.2023.134404

Publication open access: Not open

Publication channel open access: 

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/80381

Abstract

We study data-driven decision support and formalise a path from data to decision making. We focus on lot sizing in inventory management with stochastic demand and propose an interactive multi-objective optimisation approach. We forecast demand with a Bayesian model, which is based on sales data. After identifying relevant objectives relying on the demand model, we formulate an optimisation problem to determine lot sizes for multiple future time periods. Our approach combines different interactive multi-objective optimisation methods for finding the best balance among the objectives. For that, a decision maker with substance knowledge directs the solution process with one’s preference information to find the most preferred solution with acceptable trade-offs. As a proof of concept, to demonstrate the benefits of the approach, we utilise real-world data from a production company and compare the optimised lot sizes to decisions made without support. With our approach, the decision maker obtained very satisfactory solutions.

Keywords: inventory control; storehouses; optimisation; decision making; decision support systems; multivariable methods; demand; sale; supply chains; predictability; analysis; Bayesian analysis; Pareto efficiency; models (objects)

Free keywords: inventory management; data driven optimisation; multicriteria optimisation; interactive methods; Bayesian models; demand forecasting; lot sizing; Pareto optimality; decision support

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Related projects

Ministry reporting: Yes

Reporting Year: 2023

Preliminary JUFO rating: 1