Jahangirnagar University Journal of Science https://jos.ju-journal.org/jujs <p><span style="font-weight: 400;">Jahangirnagar University Journal of Science – a multi-disciplinary journal of sciences, is published twice a year, in June and in December, by the Faculty of Mathematical and Physical Sciences. Every paper is double blind reviewed by at least one appropriate referee selected by the Editorial Board. The editorial objective of the journal is facilitation of knowledge enhancement related to studies in the various fields of Mathematical and Physical Sciences.</span></p> en-US <p>©2024 Jahangirnagar University Journal of Science. All rights reserved. However, permission is granted to quote from any article of the journal, to photocopy any part or full of an article for education and/or research purpose to individuals, institutions, and libraries with an appropriate citation in the reference and/or customary acknowledgement of the journal.</p> rmzahid@juniv.edu (Professor Mohammad Zahidur Rahman) hoosain.sajjad@gmail.com (Sajjad Hossain) Fri, 08 Aug 2025 11:35:10 +0600 OJS 3.3.0.13 http://blogs.law.harvard.edu/tech/rss 60 An Efficient Approach for Estimating Unknown Constants in an Adaptive Inventory Control System under Uncertainty. https://jos.ju-journal.org/jujs/article/view/44 <p class="Abstract" style="text-align: justify;"><span style="font-size: 11.0pt; font-family: 'Times New Roman','serif';">This study focuses on inventory control in a manufacturing system for a typical machine building enterprise, involving machine building, transport, storage bunker, and assembly line. The storage bunker faces varying disturbances from the assembly line, necessitating consistent product flow from machining and transport to prevent operational failures. However, the lack of an exact machining model and uncertainties related to machine failures demand an adaptive decision-making system, which has already been developed. In this paper, we propose a modified, more realistic approach, to estimate some properties of the machining model more accurately, accounting for uncertainties due to machine failures and predictable, inconsistent disturbances from the assembly line. The effectiveness of this modified approach is demonstrated through simulation experiments.</span></p> Dr. Sushanta Kumer Roy, Mohammad Ismail Khan Copyright (c) 2025 Jahangirnagar University Journal of Science https://jos.ju-journal.org/jujs/article/view/44 Thu, 31 Jul 2025 00:00:00 +0600