Volume 18 , Issue 1 , PP: 42-56, 2022 | Cite this article as | XML | Html | PDF | Full Length Article
Maissam Jdid 1 * , Rafif Alhabib 2 , Ossama Bahbouh 3 , A. A. Salama 4 , Huda E. Khalid 5
Doi: https://doi.org/10.54216/IJNS.180105
In this paper, we present a multi-inventory with limited size model to clarify the basic idea of multi-inventory systems in order to understand the relationships between the main variables and examine the inventory’s behaviour in a very broad range. In addition to the obvious applications in physical warehouses (such as electrical equipment, supplies, raw materials used in manufacturing, etc.), there are less predictable cases in which the multi-inventory model can be used. Such a model can be applied on the number of engineers and employees in a company, also on the number of students and professors in a university, as they constitute the processes of demand, hiring, and laying off which are types of compensation. Moreover, it may be useful at times not to look at physical goods as inventory as the prior examples are both types of inventories based on the space occupied as the available space can accommodate stored materials and is considered an inventory that must be compensated when depleted. The previous examples, in addition to many others, can be classified as inventory problems indicating the abundance of inventory models application, and the possibility of benefiting from the study of inventory theory in terms of clarifying the internal structure of the systems. In this study, we used the Neutrosophic logic to solve the problem of multi-inventory and limited size, depending on the fact that the optimal volume of materials to be stored is affected by the rate of demand for inventory. Moreover, this study is considered an expansion of one of the known classical inventory models that depend on finite data and that is done by assigning a constant value to the inventory demand rate over the storage cycle time, which does not correspond with the realistic application. The limited application of classical inventory models was the motivating factor for this study as it deals with all data, whether specified or not in the inventory management process. Moreover, it considers all cases that the demand for inventory can go through, ranging from the cessation of demand for some stored materials to demand that exceeds the values provided by the real study. Through this study, we developed mathematical relationships that we used to determine the necessary quantities of each of the materials to be stored based on the rate of demand and provide us with results that are more accurate. These results that can be utilized to store many materials in appropriate quantities and available volume, ensure that there is no shortage during the storage cycle period, and enables us to calculate all the necessary costs, which will achieve great profits.
Inventory Management , Inventory Management Models , Neutrosophic Logic , Multiple Storage of Finite Materials and Volumes
[1] Alali. Ibrahim Muhammad, Operations Research. Tishreen University Publications, 2004. (Arabic version).
[2] Al Hamid .Mohammed Dabbas , Mathematical programming , Aleppo University , Syria , 2010. (Arabic version).
[3] David G . Luenbrgrr. YinyuYe, Linear and Nonlinear Programming, Springer Science & Business Media-2015.
[4] L. A. Zadeh. Fuzzy Sets. Inform. Control 8 (1965).
[5] F. Smarandache. Introduction to Neutrosophic statistics, Sitech & Education Publishing, 2014.
[6] Atanassov .k, Intuitionistic fuzzy sets. In V. Sgurev, ed., ITKRS Session, Sofia, June 1983, Central Sci. and Techn. Library, Bulg. Academy of Sciences, 1984.
[7] Smarandache, F, Neutrosophy and Neutrosophic Logic, First International Conference on Neutrosophy , Neutrosophic Logic, Set, Probability, and Statistics University of New Mexico, Gallup, NM 87301, USA,2002.
[8] Smarandache, F. A Unifying Field in Logics: Neutrosophic Logic. Neutrosophy, Neutrosophic Set, Neutrosophic Probability. American Research Press, Rehoboth, NM, 1999.
[9] Smarandache, F, Neutrosophic set a generalization of the intuitionistic fuzzy sets. Inter. J. Pure Appl. Math., 24, 287 – 297, 2005.
[10] Salama, A. A, Smarandache, F, and Kroumov, V, Neutrosophic crisp Sets & Neutrosophic crisp Topological Spaces. Sets and Systems, 2(1), 25-30, 2014.
[11] Smarandache, F. & Pramanik, S. (Eds). (2016). New trends in neutrosophic theory and applications. Brussels: Pons Editions.
[12] Alhabib.R, The Neutrosophic Time Series, the Study of Its Linear Model, and test Significance of Its Coefficients. Albaath University Journal, Vol.42, 2020. (Arabic version).
[13] Alhabib.R, Ranna.M, Farah.H and Salama, A. A, Neutrosophic Exponential Distribution. Albaath University Journal, Vol.40, 2018. (Arabic version).
[14] Alhabib.R, Ranna.M, Farah.H and Salama, A. A, studying the random variables according to Neutrosophic logic. Albaath- University Journal, Vol (39), 2017. (Arabic version).
[15] Alhabib.R, Ranna.M, Farah.H and Salama, A. A, Neutrosophic decision-making & neutrosophic decision tree. Albaath- University Journal, Vol (40), 2018. (Arabic version).
[16] Alhabib.R, Ranna.M, Farah.H and Salama, A. A, Studying the Hypergeometric probability distribution according to neutrosophic logic. Albaath- University Journal, Vol (40), 2018.(Arabic version).
[17] A. A. Salama, F. Smarandache Neutrosophic Crisp Set Theory, Educational. Education Publishing 1313 Chesapeake, Avenue, Columbus, Ohio 43212, (2015).
[18] A. A. Salama and F. Smarandache. "Neutrosophic crisp probability theory & decision making process." Critical Review: A Publication of Society for Mathematics of Uncertainty, vol. 12, p. 34-48, 2016.
[19] R. Alhabib, M. Ranna, H. Farah and A. A Salama, ''Foundation of Neutrosophic Crisp Probability Theory'', Neutrosophic Operational Research, Volume III , Edited by Florentin Smarandache, Mohamed Abdel-Basset and Dr. Victor Chang (Editors), pp.49-60, 2017.
[20] R. Alhabib, M. Ranna, H. Farah and A. A Salama.(2018). Some neutrosophic probability distributions. Neutrosophic Sets and Systems, 22, 30-38, 2018.
[21] Aslam, M., Khan, N. and Khan, M.A. (2018). Monitoring the Variability in the Process Using the Neutrosophic Statistical Interval Method, Symmetry, 10 (11), 562.
[22] Aslam, M., Khan, N. and AL-Marshadi, A. H. (2019). Design of Variable Sampling Plan for Pareto Distribution Using Neutrosophic Statistical Interval Method, Symmetry, 11 (1), 80.
[23] Aslam, M. (2019). Control Chart for Variance using Repetitive Sampling under Neutrosophic Statistical Interval System, IEEE Access, 7 (1), 25253-25262.
[24] Victor Christianto , Robert N. Boyd , Florentin Smarandache, Three possible applications of Neutrosophic Logic in Fundamental and Applied Sciences, International Journal of Neutrosophic Science, Volume 1 , Issue 2, PP: 90-95 , 2020.
[25] Madeleine Al- Tahan, Some Results on Single Valued Neutrosophic (Weak) Polygroups, International Journal of Neutrosophic Science, Volume 2 , Issue 1, PP: 38-46 , 2020.
[26] P. Singh and Y.-P. Huang. A New Hybrid Time Series Forecasting Model Based on the Neutrosophic Set
[27] and Quantum Optimization. Computers in Industry (Elsevier), 111, 121–139, 2019.
[28] R. Alhabib, A. A Salama, "Using Moving Averages To Pave The Neutrosophic Time Series'', International Journal of Neutrosophic Science (IJNS), Volume III, Issue 1, PP: 14-20, 2020.
[29] Maissam Jdid , Rafif Alhabib , A. A. Salama ," The static model of inventory management without a deficit with Neutrosophic logic", International Journal of Neutrosophic Science (IJNS), Volume 16, Issue 1, PP: 42-48, 2021.
[30] F. Smarandache, H. E. Khalid, A. K. Essa, M. Ali, “The Concept of Neutrosophic Less Than or Equal To: A New Insight in Unconstrained Geometric Programming”, Critical Review, Volume XII, 2016, pp. 72-80.
[31] F. Smarandache, H. E. Khalid, A. K. Essa, “Neutrosophic Logic: The Revolutionary Logic in Science and Philosophy”, Proceedings of the National Symposium, EuropaNova, Brussels, 2018.
[32] H. E. Khalid, “An Original Notion to Find Maximal Solution in the Fuzzy Neutrosophic Relation Equations (FNRE) with Geometric Programming (GP)”, Neutrosophic Sets and Systems, vol. 7, 2015, pp. 3-7.
[33] H. E. Khalid, “The Novel Attempt for Finding Minimum Solution in Fuzzy Neutrosophic Relational Geometric Programming (FNRGP) with (max, min) Composition”, Neutrosophic Sets and Systems, vol. 11, 2016, pp. 107-111.
[34] H. E. Khalid, F. Smarandache, A. K. Essa, (2018). The Basic Notions for (over, off, under) Neutrosophic Geometric Programming Problems. Neutrosophic Sets and Systems, 22, 50-62.
[35] H. E. Khalid, (2020). Geometric Programming Dealt with a Neutrosophic Relational Equations Under the Operation. Neutrosophic Sets in Decision Analysis and Operations Research, chapter four. IGI Global Publishing House.
[36] H. E. Khalid, “Neutrosophic Geometric Programming (NGP) with (max-product) Operator, An Innovative Model”, Neutrosophic Sets and Systems, vol. 32, 2020.
[37] H. E. Khalid, F. Smarandache, A. K. Essa, (2016). A Neutrosophic Binomial Factorial Theorem with their Refrains. Neutrosophic Sets and Systems, 14, 50-62.
[38] H. E. Khalid, A. K. Essa, (2021). The Duality Approach of the Neutrosophic Linear Programming. Neutrosophic Sets and Systems, 46, 9-23.
