A resilient supply chain model integrating demand variability and carbon emissions in imperfect production systems
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.8.03Keywords:
Energy efficient docking systems, Supply Chain Model, Carbon emission, Carbon tax, Fuzzy environment, Imperfect Production Systems, Varying demandDimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
To analyze and justify the importance of energy efficient docking systems in supply chain with varying demand along with carbon emission from warehouse electricity and fuel used in generators. A non-linear sustainable supply chain model considering a varying demand is formulated with a incorporation of a energy efficient docking systems. Due to real life unpredictable situation, Single valued trapezoidal Neutrosophic fuzzy parameters are considered in this model. Also, carbon emissions play a significant role in global warming, this paper includes the cost of carbon emissions from both warehouse electricity consumption and fuel used in generators. Lagrangian method is used to obtain the optimal solution of the problem. The proposed model has been solved with the prescribed method and it gives the average profit of the manufacturing firm with energy efficient docking systems is $1267235 and the average profit of the manufacturing firm without energy efficient docking systems is $1248710. This shows that the model with energy efficient docking systems performs better than the other one. Additionally, Single-Valued Trapezoidal Neutrosophic Numbers offer greater flexibility in capturing and representing uncertain information compared to Triangular Fuzzy Numbers, as they can model not only fuzzy uncertainty but also indeterminacy and falsity, providing a more comprehensive framework for handling complex and ambiguous data. The efficiency of energy efficient docking systems with varying demand and carbon emissions under single valued trapezoidal Neutrosophic fuzzy parameters is not yet investigated in literature.Abstract
How to Cite
Downloads
Similar Articles
- S ChandraPrabha, S. Kantha Lakshmi, P. Sivaraaj, Data analysis and machine learning-based modeling for real-time production , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- N. Anbarasi, K. Anitha, S. Hemalatha, A study on energy sum of dominating sets in East Indian states , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- R. Mercy, T. Lucia Agnes Beena, CATSEM: A Climate-Aware Time-Series Ensemble Model for Enhanced Paddy Yield Prediction , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- K. Akila, Location-specific trusted third-party authentication model for environment monitoring using internet of things and an enhancement of quality of service , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- R. Sakthiraman, L. Arockiam, RRFSE: RNN biased random forest and SVM ensemble for RPL DDoS in IoT-WSN environment , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- V. Selvi, T. S. Poornappriya, R. Balasubramani, Cloud computing research productivity and collaboration: A scientometric perspective , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Priscilla I, Jayasimman Lawrence, Enhanced Symmetric Cryptography Technique (ESCTGPU) for Secure Communication between the IoT Gateway and the public Cloud Environment , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- Somalee Mahapatra, Manoranjan Dash, Subhashis Mohanty, Adoption of artificial intelligence and the internet of things in dental biomedical waste management , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- R.R. Jenifer, V.S.J. Prakash, Detecting denial of sleep attacks by analysis of wireless sensor networks and the Internet of Things , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Josephine Theresa S, A Framework for Environment Thermal Comfort Prediction Model , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
<< < 14 15 16 17 18 19 20 21 22 23 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- U. Johns Praveena, J. Merline Vinotha, The multi-objective solid transshipment problem with preservation technology under fuzzy environment , The Scientific Temper: Vol. 16 No. 01 (2025): The Scientific Temper
- U. Johns Praveena, J. Merline Vinotha, A New Approach for Solving Bilevel Fractional/quadratic Green Transportation Problem by Implementing AI with Multi Choice Parameters Under Uncertainty , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- M. Monika, J. Merline Vinotha, A Fuzzy Supply Chain Model Evaluating Energy Management Systems under Imperfect Production and Uncertain Costs , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- U. Johns Praveena, J. Merline Vinotha, Multi-objective Solid Green Trans-shipment Problem for Cold Chain Logistics under Fuzzy Environment , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- M. Monika, J. Merline Vinotha, Optimization of a Lean Vendor–Buyer Supply Chain Model under Neutrosophic Fuzzy Environment with Transportation, Loading, and Unloading Considerations , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- U. Johns Praveena, J. Merline Vinotha, Bilevel Fractional/Quadratic Green Transshipment Problem by Implementing AI traffic control system with Multi Choice Parameters Under Fuzzy Environment , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- M. Monika, J. Merline Vinotha, A Sustainable Vendor–Buyer Supply Chain Framework Integrating Energy Storage Systems and Green Investments with Incentive Policies under Demand Uncertainty , The Scientific Temper: Vol. 17 No. 02 (2026): The Scientific Temper

