Enhance triangular fuzzy parametric framework for solid multi objective transportation problem with split decision variables
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F25%3A10258373" target="_blank" >RIV/61989100:27230/25:10258373 - isvavai.cz</a>
Result on the web
<a href="https://www.webofscience.com/wos/woscc/full-record/WOS:001539314400031" target="_blank" >https://www.webofscience.com/wos/woscc/full-record/WOS:001539314400031</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-025-10949-4" target="_blank" >10.1038/s41598-025-10949-4</a>
Alternative languages
Result language
angličtina
Original language name
Enhance triangular fuzzy parametric framework for solid multi objective transportation problem with split decision variables
Original language description
This paper introduces a novel two-step generalized parametric approach for addressing Fuzzy Multi-Objective Transportation Problems (FMOTPs), commonly encountered in logistics and transportation systems when essential parameters-such as supply, demand, and transportation costs-are uncertain. Driven by the necessity for resilient and flexible decision-making amidst uncertainty, the method employs Triangular Fuzzy Numbers (TFNs) and an accuracy parameter mu is an element of [0,1] to turn fuzzy data into precise equivalents through parametric transformation. Initially, imprecise input data are methodically converted into a sequence of Crisp Multi-Objective Transportation Problems (CMOTPs). In the subsequent phase, these CMOTPs are addressed by Fuzzy Linear Programming (FLP), and the most equitable solution at each mu-level is determined by its Euclidean distance from the fuzzy ideal solution. The suggested method is tested by numerical case studies and compared with current models-such as Nomani's approach, fuzzy DEA, and Grey Relational Analysis (GRA)-showing enhanced performance in optimality proximity, solution stability, and ranking accuracy. This research has practical applications, including improved managerial capacity to manage uncertainty, reconcile trade-offs among cost, time, and service quality, and execute robust transportation strategies in fluctuating environments. The model's scalability and openness make it suited for integration into enterprise logistics systems across industries such as manufacturing, retail, distribution, and e-commerce. The study offers a systematic and computationally efficient framework that enhances both theoretical comprehension and practical implementation of fuzzy optimization in multi-objective transportation planning.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20300 - Mechanical engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Scientific Reports
ISSN
2045-2322
e-ISSN
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Volume of the periodical
15
Issue of the periodical within the volume
1
Country of publishing house
GB - UNITED KINGDOM
Number of pages
17
Pages from-to
nestránkováno
UT code for WoS article
001539314400031
EID of the result in the Scopus database
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