پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 127 |
| تعداد شمارهها | 7,149 |
| تعداد مقالات | 76,913 |
| تعداد مشاهده مقاله | 154,946,437 |
| تعداد دریافت فایل اصل مقاله | 116,919,580 |
Integrated Supplier Selection and Inventory-Controlled Order Allocation via Fractional Programming | ||
| Industrial Management Journal | ||
| دوره 17، شماره 4، 2025، صفحه 76-99 اصل مقاله (1.02 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/imj.2025.394593.1008244 | ||
| نویسندگان | ||
| Maryam Daneshvar* 1؛ Hanieh Momeni Ruchi2؛ Seyyed Hosein Razavi Haji Agha3 | ||
| 1Assistant Prof. Department of Management, Faculty of Management and Finance, Khatam University, Tehran, Iran. | ||
| 2MSc., Department of Management, Faculty of Management and Finance, Khatam University, Tehran, Iran. | ||
| 3Associate Prof. Department of Management, Faculty of Management and Finance, Khatam University, Tehran, Iran. | ||
| چکیده | ||
| Objective: The Supply chain plays a key role in adapting the organization to variable conditions and an uncertain future. The selection of appropriate suppliers can significantly increase the competitiveness and ability of a business in the market. One of the essential factors in supply chain optimization is controlling and managing inventory cost. This paper aims to simultaneously optimize supplier selection and order allocation while considering inventory control using a fractional programming approach. Methodology: The methodology integrates quantitative analytical techniques in a multi-phase approach. First, the most frequent supplier selection criteria are identified with a literature review. The Delphi method was used to select the supplier selection criteria. In the next step, fuzzy Shannon entropy determines criterion weights. Then, fuzzy EDAS calculates supplier performance scores. Finally, fractional programming facilitates supplier selection and order allocation. Results: The most frequent supplier selection criteria were extracted from the literature review. In the Delphi technique, experts ultimately agreed on six key criteria: price, quality, delivery, flexibility, responsiveness, and financial stability. The results of the Shannon entropy analysis indicate that flexibility, with a weight of 0.20, holds the highest relative importance among the criteria. The suppliers score obtained from the fuzzy EDAS method is used as one of the parameters of the mathematical model. Conclusion: The proposed hybrid MADM approach and mathematical model have been validated using empirical data obtained from Sirjan Steel Company. The result shows that the hybrid MADM approach and fractional programming have high accuracy in selecting the best supplier. | ||
| کلیدواژهها | ||
| Supplier selection؛ order allocation؛ fractional programming؛ fuzzy MADM؛ inventory control | ||
| مراجع | ||
|
Abd El-Wahed Khalifa, H., Kumar, P., & Alodhaibi, S. S. (2022). Application of fuzzy random-based multi-objective linear fractional programming to inventory management problem. Systems Science & Control Engineering, 10(1), 90–103. https://doi.org/10.1080/21642583.2022.2040060
Abtahi, S. M., & feili, mona. (2024). Application of Multi-Objective Programming Model for Supplier Selection in Supply Chain Based on QFD Approach. Journal of Modern Management Engineering, 1, 1–33. http://sanad.iau.ir/fa/Article/1183047
Agrawal, N. (2022). Multi-criteria decision-making toward supplier selection: exploration of PROMETHEE II method. Benchmarking, 29(7), 2122–2146. https://doi.org/10.1108/BIJ-02-2021-0071
Akbari Arbatan, G., Bashokouh Ajirlou, M., Zarei, G., & Seifollahi, N. (2025). Designing a Balanced Implementation Strategy of Smart Technology in Supply Chain Management. Industrial Management Journal, 17(1), 70–98. https://doi.org/10.22059/imj.2025.382273.1008186
Alegoz, M., & Yapicioglu, H. (2019). Supplier selection and order allocation decisions under quantity discount and fast service options. Sustainable Production and Consumption, 18, 179–189. https://doi.org/10.1016/j.spc.2019.02.006
Alejo-Reyes, A., Mendoza, A., & Olivares-Benitez, E. (2021). Inventory replenishment decisions model for the supplier selection problem facing low perfect rate situations. Optimization Letters, 15, 1509–1535. https://doi.org/10.1007/s11590-019-01510-0
Alejo-Reyes, A., Olivares-Benitez, E., Mendoza, A., & Rodriguez, A. (2020). Inventory replenishment decision model for the supplier selection problem using metaheuristic algorithms. Mathematical Biosciences and Engineering, 17(3), 2016–2036. https://doi.org/10.3934/mbe.2020107
Ali, H., Zhang, J., Liu, S., & Shoaib, M. (2023). An integrated decision-making approach for global supplier selection and order allocation to create an environment-friendly supply chain. Kybernetes, 52(8), 2649–2671. https://doi.org/10.1108/K-10-2021-1046
Ali, W., Sadia, S., Ahmad, F., Javaid, S., & Abidi, N. (2025). A solution programming approaches on the multi-objective capacitated fractional transportation problem—International Journal of System Assurance Engineering and Management. https://doi.org/10.1007/s13198-024-02698-w
AmirSalami, S., & Alaei, S. (2023). Optimizing Green Supplier Selection and Order Allocation: A Fuzzy DNAP-Fuzzy TOPSIS-Bi Objective Mathematical Model Approach with Harmony Search Algorithm. Industrial Management Journal, 15(4), 650–679. https://doi.org/10.22059/imj.2023.364358.1008075
Ayough, A., Shargh, S. B., & Khorshidvand, B. (2023). A new integrated approach based on base-criterion and utility additive methods and its application to supplier selection problem. Expert Systems with Applications, 221, 119740. https://doi.org/https://doi.org/10.1016/j.eswa.2023.119740
Çabuk, S., & Erol, R. (2019). Modeling and analysis of multiple-supplier selection problem with price discounts and routing decisions. Applied Sciences, 9(17), 3480. https://doi.org/10.3390/app9173480
Chakraborty, S., Raut, R. D., Rofin, T. M., & Chakraborty, S. (2023). An integrated G-MACONT approach for healthcare supplier selection. Grey Systems: Theory and Application, 14(2), 318–336. https://doi.org/10.1108/GS-07-2023-0068
Dai, G., Zhang, X., & Zhang, R. (2025). Two-Stage Robust Optimization Approach for Supplier Selection, Development, and Order Allocation under Uncertainty. Omega, 103413. https://doi.org/https://doi.org/10.1016/j.omega.2025.103413
Davoudabadi, R., Mousavi, S. M., & Sharifi, E. (2020). An integrated weighting and ranking model based on entropy, DEA and PCA considering two aggregation approaches for resilient supplier selection problem. Journal of Computational Science, 40, 101074. https://doi.org/https://doi.org/10.1016/j.jocs.2019.101074
Erdebilli, B., Yilmaz, İ., Aksoy, T., Hacıoglu, U., Yüksel, S., & Dinçer, H. (2023). An Interval-Valued Pythagorean Fuzzy AHP and COPRAS Hybrid Methods for the Supplier Selection Problem. International Journal of Computational Intelligence Systems, 16(1), 124. https://doi.org/10.1007/s44196-023-00297-4
Ganguly, A., Kumar, C., & Chatterjee, Debdeep. (2019). A Decision-Making Model for Supplier Selection in Indian Pharmaceutical Organizations. Journal of Health Management, 21(3), 351–371. https://doi.org/10.1177/0972063419868552
Ghasemi, R., Mohaghar, A., & Dehghanian, M. M. (2025). Advancing Intelligent Supply Chain Management in the Industry 4.0 Era: A Meta-Synthesis Analysis. Industrial Management Journal, 17(2), 117–148. https://doi.org/10.22059/imj.2024.381349.1008176
Gunawan, I., Trihastuti, D., Kumar, A., & Tan, K. H. (2025). Integrated DANP and binary goal programming model in generating joint-decision making for packaging postponement and supplier selection. Annals of Operations Research, 346(2), 981–1010. https://doi.org/10.1007/s10479-023-05513-0
Güneri, B., & Deveci, M. (2023). Evaluation of supplier selection in the defense industry using q-rung orthopair fuzzy set based EDAS approach. Expert Systems with Applications, 222, 119846. https://doi.org/https://doi.org/10.1016/j.eswa.2023.119846
Hayati, E. N., Jauhari, W. A., Damayanti, R. W., & Rosyidi, C. N. (2025). An integrated analytics model for supplier selection and order allocation with machine learning and multi-criteria optimization. Decision Analytics Journal, 16, 100599. https://doi.org/https://doi.org/10.1016/j.dajour.2025.100599
Hooshmandi, M., Amiri, M., & Olfat, L. (2014). A mathematical model for supplier selection and order allocation in a supply chain considering uncertainty in design variables- for print. Industrial Management Journal, 6(1), 151–180. https://doi.org/10.22059/imj.2014.52240
İlbaş, A., Gürdere, A., & Boran, F. E. (2023). An integrated intuitionistic fuzzy set and stochastic multi-criteria acceptability analysis approach for supplier selection. Neural Computing and Applications, 35(5), 3937–3953. https://doi.org/10.1007/s00521-022-07919-6
Jafari-Raddani, M., Asgarabad, H. C., Aghsami, A., & Jolai, F. (2024). A Hybrid Approach to Sustainable Supplier Selection and Order Allocation Considering Quality Policies and Demand Forecasting: A Real-Life Case Study. Process Integration and Optimization for Sustainability, 8(1), 39–69. https://doi.org/10.1007/s41660-023-00350-x
Joshi, V., & Gupta, N. (2011). Linear fractional transportation problem with varying demand and supply. Le Matematiche, 2. https://lematematiche.dmi.unict.it/index.php/lematematiche/article/view/810
Kaur, H., & Prakash Singh, S. (2021). Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies. International Journal of Production Economics, 231, 107830. https://doi.org/10.1016/j.ijpe.2020.107830
Keshavarz-Ghorabaee, M. (2024). A multi-objective model based on group decision-making and interval-valued Pythagorean fuzzy sets for the supplier selection and order allocation problem. Industrial Management Studies, 22(74), 1–49. https://doi.org/10.22054/jims.2024.80903.2926
Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3), 435–451. https://doi.org/10.3233/INF-2015-1070
Khosroabadi, M., Gheidar-Kheljani, J., & Karimi-Gavareshki, M. H. (2024). Stochastic Modeling of Resilient Supplier Selection and Order Allocation Under Conditions of War, Sanctions, and Pandemic: An Analysis Using Bayesian Networks. Journal of Industrial Engineering Research in Production Systems, 12(24), 93–113. https://doi.org/10.22084/ier.2024.29511.2171
Kim, J. H., & Ahn, B. S. (2020). The Hierarchical VIKOR Method with Incomplete Information: Supplier Selection Problem. Sustainability, 12(22). https://doi.org/10.3390/su12229602
Koganti, V., Menikonda, N., S.P., A., Krishnaraj, T., Athhukuri, R., & Vastav, M. (2019). GRAHP TOP model for supplier selection in Supply Chain: A hybrid MCDM approach. Decision Science Letters, 8, 65–80. https://doi.org/10.5267/j.dsl.2018.5.002
Lahdhiri, M., Dhouib, A., & Mohamed, J. (2022). Multi-criteria Decision Making Using Hybrid methods for Supplier Selection in the Clothing Industry. Fibres & Textiles in Eastern Europe, 151, 23–34. https://doi.org/10.2478/ftee-2022-0004
Leong, W. Y., Wong, K. Y., & Wong, W. P. (2022). A New Integrated Multi-Criteria Decision-Making Model for Resilient Supplier Selection. Applied system innovation, 5(1), 8. 1–18. https://doi.org/10.3390/asi5010008
Manik, M. H. (2023). Addressing the supplier selection problem by using the analytical hierarchy process. Heliyon, 9(7), e17997. https://doi.org/https://doi.org/10.1016/j.heliyon.2023.e17997
Mehregan, M. R. (2016). Advanced Operation in Research.
Miar, M., Rizani, A., Pardede, R., & Basrowi, B. (2024). Analysis of the effects of capital expenditure and supply chain on economic growth and their implications on the community welfare of districts and cities in central Kalimantan province. Uncertain Supply Chain Management, 12(1), 489–504.
Modares, A., Farimani, N. M., & Emroozi, V. B. (2023). Applying a multi-criteria group decision-making method in a probabilistic environment for supplier selection (Case study: Urban railway in Iran). In Journal of Optimization in Industrial Engineering, 1(1), 129–140. https://doi.org/10.22094/joie.2023.1950386.1929
Nguyen, T., Amin, S. H., & Shah, B. (2024). A Perspective on Supplier Selection and Order Allocation: Literature Review. Administrative Sciences, 14(9). https://doi.org/10.3390/admsci14090206
Ojadi, F., Kusi-Sarpong, S., Orji, I. J., Bai, C., Gupta, H., & Okwara, U. K. (2023). A decision support framework for socially responsible supplier selection in the Nigerian banking industry. Journal of Business & Industrial Marketing, 38(10), 2220–2239. https://doi.org/10.1108/JBIM-03-2022-0139
Paul, V. K., Chakraborty, S., & Chakraborty, S. (2022). An integrated IRN-BWM-EDAS method for supplier selection in a textile industry. Decision Making: Applications in Management and Engineering, 5(2 SE-Regular articles), 219–240. https://doi.org/10.31181/dmame0307102022p
Pereira, M., Dias, E., & Fontes, D. (2019). A MCDA model for olive oil supplier selection using MACBETH. International Journal for Quality Research, 13, 849–862. https://doi.org/10.24874/IJQR13.04-07
Pérez-Domínguez, L., David, L.-C., Picón, L., A. R., L., R. R., & Yohana, S.-M. K. (2020). Suppliers' selection based on intuitionistic fuzzy dimensional analysis. Journal of Intelligent & Fuzzy Systems, 40(2), 1805–1815. https://doi.org/10.3233/JIFS-189187
Rabieh, M., Soukhakian, M. A., & Mosleh Shirazi, A. N. (2016). Two models of inventory control with supplier selection in case of multiple sourcing: a case of Isfahan Steel Company. Journal of Industrial Engineering International, 12, 243–254. https://doi.org/10.1007/s40092-016-0145-y
Rezaei, A., Rahiminezhad Galankashi, M., Mansoorzadeh, S., & Mokhtari Rafiei, F. (2020). Supplier Selection and Order Allocation with Lean Manufacturing Criteria: An Integrated MCDM and Bi-objective Modelling Approach. Engineering Management Journal, 32(4), 253–271. https://doi.org/10.1080/10429247.2020.1753490
Rezaie, B., Javadian, N., & Kazemi, M. (2025). The customer-based supplier selection and order allocation problem based on the waste management and resilience dimensions: A data-driven approach. Engineering Applications of Artificial Intelligence, 153, 110692. https://doi.org/https://doi.org/10.1016/j.engappai.2025.110692
Saputro, T. E., Figueira, G., & Almada-Lobo, B. (2023). Hybrid MCDM and simulation-optimization for strategic supplier selection. Expert Systems with Applications, 219, 119624. https://doi.org/10.1016/j.eswa.2023.119624
Shang, Z., Yang, X., Barnes, D., & Wu, C. (2022). Supplier selection in sustainable supply chains: Using the integrated BWM, fuzzy Shannon entropy, and fuzzy MULTIMOORA methods. Expert Systems with Applications, 195, 116567. https://doi.org/10.1016/j.eswa.2022.116567
Sutrisno, S., Sunarsih, S., & Widowati, W. (2022). A piecewise objective probabilistic optimization approach as decision making for supplier selection and inventory management with price discount. International Journal of Information Systems and Supply Chain Management (IJISSCM), 15(1), 1–17. https://doi.org/10.4018/IJISSCM.304089
Teymouri, E., Amiri, M., Olfat, L., & Zandieh, M. (2020). Presenting a Supplier Selection, Order Allocation, and Pricing Model in Multi-item, Single-Period, and Multi-Supplier Supply Chain Management with Surface Response Methodology and Genetic Algorithm Approach. Industrial Management Journal, 12(1), 1–23. https://doi.org/10.22059/imj.2020.285737.1007631
Ventura, J. A., Valdebenito, V. A., & Golany, B. (2013). A dynamic inventory model with supplier selection in a serial supply chain structure. European Journal of Operational Research, 230(2), 258–271. https://doi.org/10.1016/j.ejor.2013.03.012
Wang, X., Ma, H., & Su, K. (2025). Designing globalised robust supply chain work for sustainable supplier selection and order allocation. International Journal of Systems Science: Operations & Logistics, 12(1), 2532728. https://doi.org/10.1080/23302674.2025.2532728
Wei, Q., & Zhou, C. (2023). A multi-criteria decision-making framework for electric vehicle supplier selection of government agencies and public bodies in China. Environmental Science and Pollution Research, 30(4), 10540–10559. https://doi.org/10.1007/s11356-022-22783-6
Yazdani, M., Wen, Z., Liao, H., Banaitis, A., & Turskis, Z. (n.d.). A grey combined compromise solution (CoCoSo-G) method for supplier selection in construction management. Journal of Civil Engineering and Management, 25(8), 858–874. https://doi.org/10.3846/jcem.2019.11309
Ye, L., Song, G., & Song, S. (2024). Enhancing Economic, Resilient, and Sustainable Outcomes Through Supplier Selection and Order Allocation in the Food Manufacturing Industry: A Hybrid Delphi-FAHP-FMOP Method. Mathematics, 12(21). https://doi.org/10.3390/math12213312
Zandieh, M., Janatyan, N., Alem-Tabriz, A., & Rabieh, M. (2018). Designing Sustainable Distribution Network in Pharmaceutical Supply Chain: A Case Study. International Journal of Supply and Operations Management, 5(2), 122–133. https://doi.org/10.22034/2018.2.2
Ziquan, X., Jiaqi, Y., Naseem, M. H., Zuquan, X., & Xueheng, L. (2021). Supplier Selection of Shipbuilding Enterprises Based on Intuitionistic Fuzzy Multicriteria Decision. Mathematical Problems in Engineering, 2021(1), 1775053. https://doi.org/https://doi.org/10.1155/2021/1775053
| ||
|
آمار تعداد مشاهده مقاله: 290 تعداد دریافت فایل اصل مقاله: 319 |
||
سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب