https://ojs.luminescience.cn/DMA <p><em>Decision Making and Analysis</em> (DMA) is an international peer-reviewed journal and publishes research articles, reviews, case reports and conceptual papers that present theoretical, practical, statistical and modeling techniques and methods for scientific analysis so as to make informed and optimal decision. As an interdisciplinary journal, DMA welcomes manuscripts related to economics, machine learning, clinical and healthcare decision, statistical decision theory, operations research, forecasting, behavioral decision theory and cognitive psychology.</p> en-US <p>Copyright licenses detail the rights for publication, distribution, and use of research. Open Access articles published by Luminescience do not require transfer of copyright, as the copyright remains with the author. In opting for open access, the author(s) should agree to publish the article under the CC BY license (Creative Commons Attribution 4.0 International License). The CC BY license allows for maximum dissemination and re-use of open access materials and is preferred by many research funding bodies. Under this license, users are free to share (copy, distribute and transmit) and remix (adapt) the contribution, including for commercial purposes, providing they attribute the contribution in the manner specified by the author or licensor.</p> editor-dma@luminescience-press.com (Editorial Office of DMA) tech@luminescience.cn (Technician) Tue, 30 Dec 2025 14:49:52 +0800 OJS 3.3.0.7 http://blogs.law.harvard.edu/tech/rss 60 https://ojs.luminescience.cn/DMA/article/view/477 <p>Transportation problem is one of the significant linear programming problems that emerges in several conditions and gains attention of many researchers. Reducing a commodity's transportation expense to meet demand at destination is the goal of the transportation problem. However, uncertainty plays a vital role in real life, making it challenging for decision-makers to provide precise values for the coefficients related to the transportation problem. Hesitant bifuzzy sets are a notable advancement of fuzzy set theory, as they allow decision-makers to deal with every hesitancy without any restriction. This study aims to introduce a formulation of transportation problem under a hesitant bifuzzy environment. In this study, we have introduced a novel Russel approximation method (RAM) for the hesitant bifuzzy transportation problem, where every parameter is represented by hesitant bifuzzy elements. To show the applicability of the proposed method, a real-life illustration has been taken in this article. Additionally, to demonstrate the superiority of the proposed method, a comparative study has also been conducted with other existing methods, which results in the minimum transportation cost.</p> Ismat Beg, Soniya Gupta, Arpa Ghosh, Dheeraj Kumar Joshi Copyright © 2025 Ismat Beg, Soniya Gupta, Arpa Ghosh, Dheeraj Kumar Joshi https://creativecommons.org/licenses/by/4.0 https://ojs.luminescience.cn/DMA/article/view/477 Tue, 30 Dec 2025 00:00:00 +0800