Analysis of a Demand-Driven Production Inventory Model in a Trapezoidal Neutrosophic Number-Ruled Decision Environment
Abstract
An Economic Production Quantity (EPQ) model is built with fundamental intuitions that time influences demand pattern and demand can control production in manufacturing process. Also, existence of deterioration of produced items during warehousing is considered. Preservation technology is installed for lowering the deterioration rate as much as possible. The manufacturing-warehousing process includes ambiguities in several pockets of decision-making phenomena. Trapezoidal neutrosophic number describes the imprecise environment for decision phenomena in this paper. Numerical results reveal that the cost reduction goal is impacted negatively for large size of production potential and for much reliance of the production process on demand pattern. On contrary, incorporations of preservation measure and neutrosophic decision phenomena favor the cost minimization objective.
References
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M. Namakshenas, and M. Mahdavi Mazdeh, “A Mathematical Model for Production and Inventory Management of Time-sensitive Pharmaceutical in a Molecular Imaging Center,“ Journal of Decisions and Operations Research, vol. 6, no. 2, pp. 174-182, 2021.
A. A. Taleizadeh, V. R. Soleymanfar, and K. Govindan, “Sustainable economic production quantity models for inventory systems with shortage,“ Journal of cleaner production, vol. 174, no. , pp. 1011-1020, 2018.
A. A. Taleizadeh, M. S. Naghavi-Alhoseiny, L. E. Cárdenas-Barrón, and A. Amjadian, “Optimization of price, lot size and backordered level in an EPQ inventory model with rework process,“ RAIRO-Operations Research, vol. 58, no. 1, pp. 803-819, 2024.
A. Farahbakhsh, and A. S. Kheirkhah, “A new efficient genetic algorithm-Taguchi-based approach for multi-period inventory routing problem,” International journal of research in industrial engineering, vol. 12, no. 4, pp. 397-413, 2023.
A.H. Nobil, E. Nobil, A.H.A. Sedigh, L.E. Cárdenas-Barrón, D. Garza-Núñez, G. Treviño-Garza, and N.R. Smith, “Economic production quantity models for an imperfect manufacturing system with strict inspection,” Ain Shams Engineering Journal, vol. 102714, 2024.
M. Rahaman, S. Alam, R. Haque, A. A. Shaikh, P. K. Behera, and S. P. Mondal, “An economic production quantity model for an imperfect production system with selling price, advertisement frequency and green-level dependent demand,” Electronic Commerce Research, pp. 1-28, 2024.
R. Haque, M. Pervin, and S. P. Mondal, “A sustainable manufacturing-remanufacturing inventory model with price and green sensitive demand for defective and usable items,” RAIRO-Operations Research, vol. 58, no. 4, pp. 3439–3467, 2024.
M. Muthuswamy, A. M. Ali, “Sustainable supply chain management in the age of machine intelligence: addressing challenges, capitalizing on opportunities, and shaping the future landscape,” Sustainable Machine Intelligence Journal, vol. 3, pp. 1-14, 2023.
J. Ghahremani-Nahr, A. Ghaderi, and R. Kian, “Bi-objective fuzzy food bank network design with considering freshness of food baskets,” Journal of applied research on industrial engineering, vol. 10, no. 4, pp. 518-540, 2023.
I. Badi, M. B. Bouraima, Z. Stević, E. A. Oloketuyi, and O. O. Makinde, “Optimizing vendor-managed inventory in multi-tier distribution systems,” Spectrum of operational research, vol. 1, no. 1, pp. 33-43, 2024.
L. A. Zadeh, “Fuzzy sets,” Information and control, vol. 8, no. 3, pp. 338-353, 1965.
L. A. Zadeh, “The concept of a linguistic variable and its application to approximate reasoning,” Information sciences, vol. 8, no 3, pp. 199-249, 1975.
R. E. Moore, “Interval analysis,” Englewood Cliffs: prentice-Hall, vol. 4, pp. 8-13, 1966.
D. Dubois, and H. Prade, H. "Fuzzy sets and systems: Theory and applications," Mathematics in Science and Engineering, vol. 144, Academic Press, 1980.
K. T. Atanassov, "Intuitionistic fuzzy sets." Fuzzy Sets and Systems, vol. 20, no. 1, pp. 87–96, 1986.
F. Smarandache, Neutrosophy: Neutrosophic Probability, Set, and Logic. American Research Press, 1998.
P. Sing, M. Rahaman, and S. P. Sankar, “Solution of fuzzy system of linear equation under different fuzzy difference ideology,” Spectrum of operational research, vol. 1, no. 1, 64-74, 2024.
A. Alamin, M. Rahaman, and S. P. Mondal, “Geometric Approach for Solving First Order Non-Homogenous Fuzzy Difference Equation,” Spectrum of Operational Research, vol. 2, no. 1, 61-71, 2025.
A. Biswas, K. H. Gazi, S. P. Mondal, and A. Ghosh, “A decision-making framework for sustainable highway restaurant site selection: Ahp-topsis approach based on the fuzzy numbers,” Spectrum of operational research, vol. 2, no. 1, pp. 1-26, 2025.
K. H. Gazi, N. Raisa, A. Biswas, F. Azizzadeh, and S. P. Mondal, “Finding the Most Important Criteria in Women's Empowerment for Sports Sector by Pentagonal Fuzzy DEMATEL Methodology,” Spectrum of Decision Making and Applications, vol. 2, no. 1, 28-52, 2025.
R. Imran, K. Ullah, Z. Ali, and M. Akram, “A multi-criteria group decision-making approach for robot selection using interval-valued intuitionistic fuzzy information and aczel-alsina bonferroni means,” Spectrum of Decision Making and Applications, vol. 1, no. 1, pp. 1-32, 2024.
B. Ghrissi, A. Amara, and Y. Henka, “Higher-order fuzzy fractional differential equations: on the existence, uniqueness and Hyers–Ulam–Rassias stability of solutions,” Journal of Fuzzy Extension and Applications, vol. 5, no. 3, pp. 353-364, 2024.
S. Mukherjee, A. Kumar, and S. Kumbhakar, “Numerical simulation of fuzzy fractional differential equations using a reliable technique,” Journal of Fuzzy Extension and Applications, vol. 5, no. 2, pp. 159-172, 2024.
S. A. M. Zubair, “Single-valued neutrosophic uncertain linguistic set based on multi-input relationship and semantic transformation,” Journal of fuzzy extension and applications, vol. 4, no. 4, pp. 257-270, 2023.
S. A. Edalatpanah, H. A. E. W. Khalifa, A. Al-Quran, F. Al-Sharqi, Z. Rodzi, and A. Lutfi, “Enhancing neutrosophic fuzzy goal programming approach for solving multiobjective probabilistic linear programming problems,” Full Length Article, vol. 23, no. 1, pp. 312-12, 2023.
A. Naseem, M. Akram, K. Ullah, and Z. Ali, “Aczel-Alsina aggregation operators based on complex single-valued neutrosophic information and their application in decision-making problems,” Decision Making Advances, vol. 1, no. 1, pp. 86-114, 2023.
S. A. Edalatpanah, and F. Smarandache, “Data envelopment analysis for simplified neutrosophic sets,” Infinite Study, 2019.
S. Bodur, S. Topal, H. Gürkan, and S. S. Edalatpanah, “A Novel Neutrosophic Likert Scale Analysis of Perceptions of Organizational Distributive Justice via a Score Function: A Complete Statistical Study and Symmetry Evidence Using Real-Life Survey Data,” Symmetry, vol. 16, no. 5, pp. 598, 2024.
R. Rasinojehdehi, and H. B. Valami, “A comprehensive neutrosophic model for evaluating the efficiency of airlines based on SBM model of network DEA,” Decision making: applications in management and engineering, vol. 6, no. 2, pp. 880-906, 2023.
K. S. Park, “Fuzzy-set theoretic interpretation of economic order quantity,” IEEE Transactions on systems, Man, and Cybernetics, vol. 17, no. 6, pp. 1082-1084, 1987.
S. Bag, D. Chakraborty, and A. R. Roy, “A production inventory model with fuzzy random demand and with flexibility and reliability considerations,” Computers & Industrial Engineering, vol. 56, no. 1, pp. 411-416, 2009.
S. K. De, and S. S. Sana, “Fuzzy order quantity inventory model with fuzzy shortage quantity and fuzzy promotional index,” Economic Modelling, vol. 31, pp. 351-358, 2013.
G. C. Mahata, S. K. De, K. Bhattacharya, S. Maity, “Three-echelon supply chain model in an imperfect production system with inspection error, learning effect, and return policy under fuzzy environment,” International Journal of Systems Science: Operations & Logistics, vol. 10, no. 1, pp. 1962427, 2023.
C. Jain, R. K. Saini, and A. Sangal, “Application of Trapezoidal Fuzzy Numbers in the Inventory Problem of Decision Science,” Multicriteria Algorithms with Applications, vol. 3, pp. 1-14, 2024.
H. Barman, M. Pervin, and S. K. Roy, “Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic,” RAIROoperations Research, vol. 56, no. 4, 2245-2275, 2022.
B. K. Debnath, P. Majumder, and U. K. Bera, “Multi-objective sustainable fuzzy economic production quantity (SFEPQ) model with demand as type-2 fuzzy number: A fuzzy differential equation approach,” Hacettepe Journal of Mathematics and Statistics, vol. 48, no. 1, pp. 112-139, 2019.
T. Garai, D. Chakraborty, and T. K. Roy, “A multi-item generalized intuitionistic fuzzy inventory model with inventory level dependent demand using possibility mean, variance and covariance,” Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 1021-1036, 2018.
A. F. Momena, M. Rahaman, R. Haque, S. Alam, and S. P. Mondal, “A learning-based optimal decision scenario for an inventory problem under a price discount policy,” Systems, vol. 11, no. 5, pp. 235, 2023.
S. Karmakar, S. K. De, and A. Goswami, “A pollution sensitive remanufacturing model with waste items: triangular dense fuzzy lock set approach,” Journal of Cleaner Production, vol. 187, pp. 789-803, 2018.
A. K. Maiti, “Cloudy fuzzy inventory model under imperfect production process with demand dependent production rate,” Journal of Management Analytics, vol. 8, no. 4, pp. 741-763, 2021.
M. Rahaman, S. P. Mondal, S. Alam, S., S. K. De, “A study of a lock fuzzy EPQ model with deterioration and stock and unit selling price-dependent demand using preservation technology,” Soft Computing, vol. 26, no. 6, pp. 2721-2740, 2022.
S. K. Das, “A fuzzy multi objective inventory model of demand dependent deterioration including lead time,” Journal of fuzzy extension and applications, vol. 3, no. 1, pp. 1-18, 2022.
H. Barman, M. Pervin, S. K. Roy, and G. W. Weber, “Back-ordered inventory model with inflation in a cloudy-fuzzy environment,” Journal of Industrial & Management Optimization, vol. 17, no. 4, pp. 1913-1941, 2021.
M. Rahaman, S. Maity, S. K. De, S. P. Mondal, and S. Alam, “Solution of an Economic Production Quantity model using the generalized Hukuhara derivative approach,” Scientia Iranica 2021.
A. K. Manna, M. S. Rahman, A. A. Shaikh, A. K. Bhunia, and I. Konstantaras, “Modeling of a carbon emitted production inventory system with interval uncertainty via metaheuristic algorithms,” Applied Mathematical Modelling, vol. 106, pp. 343-368, 2022.
S. Maity, A. Chakraborty, S. K. De, and M. Pal, “A study of an EOQ model of green items with the effect of carbon emission under pentagonal intuitionistic dense fuzzy environment,” Soft Computing, vol. 27, no. 20, pp. 15033-15055, 2023.
M. Rahaman, R. Haque, S. Alam, S. Zupok, S. Salahshour, F. Azizzadeh, and S. P. Mondal, “Solvability criteria for uncertain differential equations and their applicability in an economic lot-size model with a type-2 interval phenomenon,” Symmetry, vol. 15, no. 10, pp. 1883, 2023.
A. Chakraborty, S. P. Mondal, A. Ahmadian, N. Senu, S. Alam, and S. Salahshour, “Different forms of triangular neutrosophic numbers, de-neutrosophication techniques, and their applications,” Symmetry, vol. 10, no. 8, pp. 327, 2018.
S. A. Bhat, “An enhanced AHP group decision-making model employing neutrosophic trapezoidal numbers,” J. Oper. Strateg Anal, vol. 1, no. 2, pp. 81-89, 2023.
A. Chakraborty, S. P. Mondal, A. Mahata, and S. Alam, “Different linear and non-linear form of trapezoidal neutrosophic numbers, de-neutrosophication techniques and its application in time-cost optimization technique, sequencing problem,” RAIRO-Operations Research, vol. 55, pp. S97-S118, 2021.
A. Chakraborty, “A New Score Function of Pentagonal Neutrosophic Number and its Application in Networking Problem,” International Journal of Neutrosophic Science, vol. 1, no. 1, pp 35-46, 2020.
K. K. Mohanta, and O. Toragay, O. “Enhanced performance evaluation through neutrosophic data envelopment analysis leveraging pentagonal neutrosophic numbers,” Journal of operational and strategic analytics, vol. 1, no. 2, pp. 70-80, 2023.
S. A. Edalatpanah, “Neutrosophic structured element,” Expert systems, vol. 37, no. 5, pp. e12542, 2020.
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Published
2024-12-09
How to Cite
RAHAMAN, Mostafijur et al.
Analysis of a Demand-Driven Production Inventory Model in a Trapezoidal Neutrosophic Number-Ruled Decision Environment.
Yugoslav Journal of Operations Research, [S.l.], v. 35, n. 4, p. 797-836, dec. 2024.
ISSN 2334-6043.
Available at: <https://yujor.fon.bg.ac.rs/index.php/yujor/article/view/1314>. Date accessed: 22 nov. 2025.
doi: https://doi.org/10.2298/YJOR240515052R.
Issue
Section
Research Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
