20.500.12556/DKUM-96931 Improved Whale Optimization Algorithm for supply chain financial risk assessment of cloud warehouse platform This study provides an in-depth analysis of a new financial model for cloud warehouses and evaluates the associated credit risk within the context of supply chain financing, focusing on the intelligent transformation in this field. Concurrently, an optimization problem was derived from the evaluation issue, with the whale optimization algorithm (WOA) used to identify a reasonable default point and distance. To simplify the identification of these points, we enhanced the traditional WOA, resulting in an improved version, the IWOA, which demonstrated very good optimization performance. The IWOA's optimization capabilities were applied to determine the optimal ratio of short- and long-term debt coefficients, identifying the default point in the Kealhofer, McQuown, and Vasicek (KMV) credit monitoring model, replacing fixed values and yielding more precise results. Furthermore, this study introduces a novel analytical approach to credit risk measurement, advancing the development of related theories and methods. Accurate analysis of financial stability and risk is crucial in industrial sectors, including engineering and manufacturing. The simulation using specific data revealed that the IWOA-KMV model exhibited better and faster optimization capabilities, with greater discrimination ability compared to the KMV model. Overall, this study examines the risk factors in the cloud warehouse financing model, offers an improved version of the WOA, introduces a modified IWOA-KMV model to create a scientific, practical credit risk assessment framework, and provides guidance for risk control in cloud warehouse financing, a novel financing service. cloud warehouse platform supply chain finance risk assessment KMV model swarm intelligence improved Whale Optimization Algorithm platforma skladišča v oblaku ocena tveganja inteligenca rojev optimizacija true false true Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering Angleški jezik Slovenski jezik https://apem-journal.org/ Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Članek v reviji 2026-02-03 09:10:51 2026-02-03 09:10:52 2026-02-04 03:11:25 0000-00-00 00:00:00 2024 0 0 str. 395-407 no. 3 Vol. 19 Sept. 2024 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2024-09-19 2024-10-15 2024-10-31 004.8 267065603 10.14743/apem2024.3.515 1854-6250 APEM19-3_395-407.pdf APEM19-3_395-407.pdf 1 418D80598FC1D7D2E5F1C7FB7105EBBF 5006b5001bbc4e51761d36375ce71cd60095b55ef24a3ed7ebed13fb6b2d4b41 697dec3e-00d8-11f1-bf34-00155d581219 https://dk.um.si/Dokument.php?lang=slv&id=203011 https://apem-journal.org/Archives/2024/Abstract-APEM19-3_395-407.html 0 6e106d9b-00d8-11f1-bf34-00155d581219 https://dk.um.si/Dokument.php?lang=slv&id=203012 Fakulteta za strojništvo Advances in production engineering & management 0 0 0