Implementation of the decision making along with analytic hierarchy process (AHP) approaches in the assessment of the petroleum products cost based on the statical model
DOI:
https://doi.org/10.15587/1729-4061.2022.263192Keywords:
AHP, decision-making-statistical model, petroleum, cost, PDS, crude oilAbstract
In this study, the investigation of the decision-making strategy was used to select the alternative that was finally adopted in the crude oil refining process. This strategy was used to select the option that was ultimately implemented in the process. The Doura industrial refinery was the source of the information that was acquired for the analysis. The super decision software was applied in order to carry out an examination of the PDS components. After going through the process of refining, one can get the items on the following list: There are five main types of petroleum products, and they are: gasoline, gas oil, liquid gas, black oil, and white oil. Gasoline is the most common type of petroleum product. In order for the parameters to be optimally accommodated by the solution that is finally decided to be the most practical one, the analytic hierarchy process, also known as AHP, technique has been applied. This has been done in conjunction with the parameter determination system, or PDS. This has been done in order to reach the maximum potential level of productivity in the most efficient manner. As a result of the fact that this was the circumstance, a probe into the preliminary phase of the project was carried out, which in the end resulted in the expenditure of a grand total of 3969463 USD. This was determined by taking into account the costs of running the firm in addition to the prices of the raw materials that were utilized in the production process. In addition, the output of the refining process was not only dependent on the price and quantity of the product, but also on the amount of product that was actually sold. This meant that the cost and quantity of the product were not the only factors that determined the output. In order to determine what should be done during the process of making an estimate of what should be done in order to arrive at the response that was going to be the most advantageous taking everything into consideration, a mathematical model was applied as part of the process.
References
- Zhang, H., Kou, G., Peng, Y. (2019). Soft consensus cost models for group decision making and economic interpretations. European Journal of Operational Research, 277 (3), 964–980. doi: https://doi.org/10.1016/j.ejor.2019.03.009
- Saługa, P. W., Szczepańska-Woszczyna, K., Miśkiewicz, R., Chłąd, M. (2020). Cost of Equity of Coal-Fired Power Generation Projects in Poland: Its Importance for the Management of Decision-Making Process. Energies, 13 (18), 4833. doi: https://doi.org/10.3390/en13184833
- Lu, Y., Xu, Y., Herrera-Viedma, E., Han, Y. (2021). Consensus of large-scale group decision making in social network: the minimum cost model based on robust optimization. Information Sciences, 547, 910–930. doi: https://doi.org/10.1016/j.ins.2020.08.022
- Brouwer, W., van Baal, P., van Exel, J., Versteegh, M. (2018). When is it too expensive? Cost-effectiveness thresholds and health care decision-making. The European Journal of Health Economics, 20 (2), 175–180. doi: https://doi.org/10.1007/s10198-018-1000-4
- Hansen, K. (2019). Decision-making based on energy costs: Comparing levelized cost of energy and energy system costs. Energy Strategy Reviews, 24, 68–82. doi: https://doi.org/10.1016/j.esr.2019.02.003
- Li, F., Zhu, Q., Chen, Z. (2019). Allocating a fixed cost across the decision making units with two-stage network structures. Omega, 83, 139–154. doi: https://doi.org/10.1016/j.omega.2018.02.009
- Rodríguez, R. M., Labella, Á., Dutta, B., Martínez, L. (2021). Comprehensive minimum cost models for large scale group decision making with consistent fuzzy preference relations. Knowledge-Based Systems, 215, 106780. doi: https://doi.org/10.1016/j.knosys.2021.106780
- Sun, Q., Wu, J., Chiclana, F., Fujita, H., Herrera-Viedma, E. (2022). A Dynamic Feedback Mechanism With Attitudinal Consensus Threshold for Minimum Adjustment Cost in Group Decision Making. IEEE Transactions on Fuzzy Systems, 30 (5), 1287–1301. doi: https://doi.org/10.1109/tfuzz.2021.3057705
- Zhang, B., Liang, H., Gao, Y., Zhang, G. (2018). The optimization-based aggregation and consensus with minimum-cost in group decision making under incomplete linguistic distribution context. Knowledge-Based Systems, 162, 92–102. doi: https://doi.org/10.1016/j.knosys.2018.05.038
- Van Schaik, G. W. W., Van Schaik, K. D., Murphy, M. C. (2018). Point‐of‐Care Ultrasonography (POCUS) in a Community Emergency Department: An Analysis of Decision Making and Cost Savings Associated With POCUS. Journal of Ultrasound in Medicine, 38 (8), 2133–2140. doi: https://doi.org/10.1002/jum.14910
- Jafari-Marandi, R., Khanzadeh, M., Tian, W., Smith, B., Bian, L. (2019). From in-situ monitoring toward high-throughput process control: cost-driven decision-making framework for laser-based additive manufacturing. Journal of Manufacturing Systems, 51, 29–41. doi: https://doi.org/10.1016/j.jmsy.2019.02.005
- Vega, M. A., Todd, M. D. (2020). A variational Bayesian neural network for structural health monitoring and cost-informed decision-making in miter gates. Structural Health Monitoring, 21 (1), 4–18. doi: https://doi.org/10.1177/1475921720904543
- Wang, F., Yeap, S. P. (2021). Using magneto-adsorbent for methylene Blue removal: A decision-making via analytical hierarchy process (AHP). Journal of Water Process Engineering, 40, 101948. doi: https://doi.org/10.1016/j.jwpe.2021.101948
- Doke, A. B., Zolekar, R. B., Patel, H., Das, S. (2021). Geospatial mapping of groundwater potential zones using multi-criteria decision-making AHP approach in a hardrock basaltic terrain in India. Ecological Indicators, 127, 107685. doi: https://doi.org/10.1016/j.ecolind.2021.107685
- Sharaf, H. K., Ishak, M. R., Sapuan, S. M., Yidris, N. (2020). Conceptual design of the cross-arm for the application in the transmission towers by using TRIZ–morphological chart–ANP methods. Journal of Materials Research and Technology, 9 (4), 9182–9188. doi: https://doi.org/10.1016/j.jmrt.2020.05.129
- Sharaf, H. K., Ishak, M. R., Sapuan, S. M., Yidris, N., Fattahi, A. (2020). Experimental and numerical investigation of the mechanical behavior of full-scale wooden cross arm in the transmission towers in terms of load-deflection test. Journal of Materials Research and Technology, 9 (4), 7937–7946. doi: https://doi.org/10.1016/j.jmrt.2020.04.069
- Salman, S., Sharaf, H. K., Hussein, A. F., Khalaf, N. J., Abbas, M. K., Aned, A. M. et. al. (2022). Optimization of raw material properties of natural starch by food glue based on dry heat method. Food Science and Technology, 42. doi: https://doi.org/10.1590/fst.78121
- Wu, Z., Tu, J. (2021). Managing transitivity and consistency of preferences in AHP group decision making based on minimum modifications. Information Fusion, 67, 125–135. doi: https://doi.org/10.1016/j.inffus.2020.10.012
- Foroozesh, F., Monavari, S. M., Salmanmahiny, A., Robati, M., Rahimi, R. (2022). Assessment of sustainable urban development based on a hybrid decision-making approach: Group fuzzy BWM, AHP, and TOPSIS–GIS. Sustainable Cities and Society, 76, 103402. doi: https://doi.org/10.1016/j.scs.2021.103402
- Wang, C.-N., Nguyen, N.-A.-T., Dang, T.-T., Lu, C.-M. (2021). A Compromised Decision-Making Approach to Third-Party Logistics Selection in Sustainable Supply Chain Using Fuzzy AHP and Fuzzy VIKOR Methods. Mathematics, 9 (8), 886. doi: https://doi.org/10.3390/math9080886
- Santos, M. dos, Costa, I. P. de A., Gomes, C. F. S. (2021). Multicriteria decision-making in the selection of warships: a new approach to the AHP method. International Journal of the Analytic Hierarchy Process, 13 (1). doi: https://doi.org/10.13033/ijahp.v13i1.833
- Vinogradova-Zinkevič, I., Podvezko, V., Zavadskas, E. K. (2021). Comparative Assessment of the Stability of AHP and FAHP Methods. Symmetry, 13 (3), 479. doi: https://doi.org/10.3390/sym13030479
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Nada Salman Nikkeh, Suhair Muafaq Abdulhussein, Mohammed Ali Mohammed
This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.
A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.