مهندسی سیستم و بهره‌وری

مهندسی سیستم و بهره‌وری

مدل‌سازی چندهدفه برای مدیریت هزینه در تخصیص بهینه کالاهای امدادی در شرایط بحرانی

نوع مقاله : پژوهشی

نویسندگان
1 دانشجوی دکتری، گروه مدیریت صنعتی، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران
2 نویسنده مسئول: استادیار، گروه مدیریت صنعتی، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران
چکیده
این تحقیق به بررسی مدل‌سازی چندهدفه برای مدیریت هزینه در تخصیص بهینه کالاهای امدادی در شرایط بحرانی می‌پردازد، با تمرکز بر اهمیت زمان و منابع در مواقع اضطراری. هدف اصلی، توسعه مدل ریاضی برای بهینه‌سازی تخصیص مؤثر کالاها با اعمال عدم‌قطعیت، کاهش هزینه‌ها و بهبود پاسخگویی به بحران‌هاست. مقاله یک مدل برنامه‌ریزی ریاضی چندهدفه و چنددوره‌ای برای توزیع منصفانه اقلام امدادرسانی ارائه می‌دهد و یک زنجیره تأمین بشردوستانه چندهدفه و چندسطحی برای توزیع عادلانه بسته‌های معیشتی توسعه یافته است. علاوه بر این، روش فراابتکاری برای حل مدل در ابعاد بزرگ و ارزیابی راه‌حل‌های پارتویی انجام شده است. تحقیق چهار شاخص لجستیک بشردوستانه را بررسی می‌کند: هزینه دسترسی و حمل‌ونقل، نرخ تقاضای برآورده نشده در هر دوره، فاصله بین نرخ پر کردن تقاضا و رضایت ایده‌آل در کل دوره، و خطرات زیست‌محیطی. مدل برای تخصیص مواد ضروری (آب، غذا، دارو، تجهیزات، پوشاک و پتو) از مراکز امدادرسانی چندگانه به مناطق آسیب‌دیده مختلف طراحی شده تا رفتار منصفانه‌ای داشته باشد و با وضعیت واقعی سازگارتر باشد. نتایج نشان می‌دهد که افزایش اپسیلون تا مقدار مشخصی تغییرات کمی در توابع هدف ایجاد می‌کند، اما پس از آن تغییرات قابل‌ملاحظه‌ای رخ می‌دهد؛ ناحیه شدنی و بردار بهبوددهنده برای اپسیلون بین ۵۰ تا ۹۰۰ تعیین شده و مقادیر بهینه اپسیلون برای توابع هدف اول تا چهارم به ترتیب ۵۰۰، ۱۵۰، ۶۰۰، و ۱۵۰ و ۶۰۰ است. مدل برای بلایای طبیعی ناگهانی محلی در مقیاس بزرگ در مناطق شهری مناسب است و مستقیماً برای طوفان‌ها یا بلایای پراکنده قابل استفاده نیست. در نهایت، این تحقیق به بهبود فرآیندهای امدادرسانی، کاهش هزینه‌ها و نجات جان انسان‌ها کمک می‌کند.

تازه های تحقیق

  • توسعه مدل ریاضی چندهدفه تحت عدم‌قطعیت برای تخصیص بهینه منابع امدادی
  • استفاده از روش فراابتکاری پیشرفته برای حل مدل چندسطحی و چنددوره‌ای
  • طراحی مدل با هدف تضمین توزیع منصفانه بسته‌های معیشتی
  • توانایی مدل در کاهش هزینه‌ها و بهبود پاسخگویی سریع در بلایای محلی

کلیدواژه‌ها
موضوعات

عنوان مقاله English

Multi-objective Modeling for Cost Management in Optimal Allocation of Relief Supplies in Crisis Conditions

نویسندگان English

Somayeh Khoshnami 1
Elmira Mashayekhi 2
1 Ph.D. Student, Department of Industrial Management, Qa. C., Islamic Azad University, Qazvin, Iran
2 Corresponding author: Assistant Professor, Department of Industrial Management, Qa. C., Islamic Azad University, Qazvin, Iran
چکیده English

This study examines multi-objective modeling for cost management in the optimal allocation of relief goods in crisis situations, focusing on the importance of time and resources in emergencies. The main goal is to develop a mathematical model for optimization that enables more effective and efficient allocation of relief goods by incorporating uncertainty in decision-making, reducing costs, and improving crisis response. The article presents a multi-objective, multi-period mathematical programming model for fair distribution of relief items and develops a multi-objective, multi-level humanitarian supply chain for equitable distribution of livelihood packages to counter crises. Additionally, a metaheuristic method is developed to solve the model for large-scale problems, and Pareto solutions are evaluated. The research examines four dimensions of humanitarian logistics indicators: access and transportation costs, unmet demand rate per period, the distance between the demand fill rate and the ideal satisfaction rate over the entire period, and environmental risks. The model is designed for allocating essential materials (water, food, medicine, equipment, clothing, and blankets) from multiple relief centers to various affected areas to ensure fair behavior and better alignment with real conditions. Results show that increasing epsilon up to a certain value causes negligible changes in objective function values, but beyond that, it leads to significant changes; the feasible region and improvement vector for objective functions are determined for epsilon values between 50 and 900, with optimal epsilon values for the first to fourth objective functions being 500, 150, 600, and 150 and 600, respectively. The proposed model is suitable for sudden large-scale local natural disasters (not national) occurring in urban areas with a certain resident population and cannot be directly used for storms or other low-impact, dispersed disasters. Ultimately, this research helps improve relief processes, reduce associated costs, and leads to saving human lives and mitigating crisis damages.

کلیدواژه‌ها English

Cost Management
Relief Distribution
Crisis Conditions
Epsilon Constraint
Multi-objective Modelling

Copyright © Somayeh Khoshnami, Elmira Mashayekhi

 

License

This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.

Abolghasemian, M., Ghane Kanafi, A., & Daneshmandmehr, M. (2020). A two-phase simulation-based optimization of hauling system in open-pit mine. International Journal of Management Studies, 13(4), 705–732. https://doi.org/10.22059/ijms.2020.294809.673898
Aghajani, M., Torabi, S. A., & Heydari, J. (2020). A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains. Socio-Economic Planning Sciences, 71, 100780. https://doi.org/10.1016/j.seps.2019.100780
Avazpour, M., Zarei, J., & Alinezhad, E. (2025). Evaluation and prioritization of electricity generation technologies in Iran using a multi-criteria decision-making approach. System Engineering and Productivity5(3), 179-198 (In Persian). https://doi.org/10.22034/sep.2025.2063697.1333
Boonmee, C., Arimura, M., & Asada, T. (2017). Facility location optimization model for emergency humanitarian logistics. International Journal of Disaster Risk Reduction, 24, 485–498. https://doi.org/10.1016/j.ijdrr.2017.01.017
Cao, C., Liu, Y., Tang, O., & Gao, X. (2021). A fuzzy bi-level optimization model for multi-period post-disaster relief distribution in sustainable humanitarian supply chains. International Journal of Production Economics, 235, 108081. https://doi.org/10.1016/j.ijpe.2021.108081
Eghbal, F., Ehsanifar, M., Mirhosseini, M., & Mazaheri, H. (2025). Identification and Modeling of key factors significant to the financial performance of Iranian construction Companies. System Engineering and Productivity4(4), 77-94 (In Persian). https://doi.org/10.22034/msb.2024.2034092.1218
Ghahremani-Nahr, J., Nozari, H., & Szmelter-Jarosz, A. (2024). Designing a humanitarian relief logistics network considering the cost of deprivation using a robust-fuzzy-probabilistic planning method. Journal of International Humanitarian Action, 9(1), 19. https://doi.org/10.1186/s41018-024-00163-8
Gholsheikh, N. G, Sanavi Garousiyan, V., & Hosseinzadeh, A. (2025). Design and validation of smart customer experience in Agricultural Bank of Khorasan Razavi Province with a mixed-methods approach. System Engineering and Productivity5(1), 65-91 (In Persian). https://doi.org/10.22034/sep.2025.2049020.1244
Jahangiri, S., Abolghasemian, M., Ghasemi, P., & Pourghader Chobar, A. (2023). Simulation-based optimisation: Analysis of the emergency department resources under COVID-19 conditions. International Journal of Industrial and Systems Engineering, 43(1), 1–19. https://doi.org/10.1504/IJISE.2023.128399
Jahangiri, S., Abolghasemian, M., Pourghader Chobar, A., Nadaffard, A., & Mottaghi, V. (2021). Ranking of key resources in the humanitarian supply chain in the emergency department of Iranian hospital: A real case study in COVID-19 conditions. Journal of Applied Research on Industrial Engineering, 8(Special Issue), 1–10. https://doi.org/10.22105/jarie.2021.275255.1263
Kanoun, I., Chabchoub, H., & Aouni, B. (2010). Goal programming model for fire and emergency service facilities site selection. INFOR: Information Systems and Operational Research, 48(3), 143–153. https://doi.org/10.3138/infor.48.3.143
Karimi Zarachi, M., Fathi, M. R., Raeesi Nafchi, S., & Hosseini Zarch, S. M. (2023). The impact of supply chain relationship quality on knowledge sharing and innovation performance in the packaging industry. System Engineering and Productivity3(3), 63-81 (In Persian). https://doi.org/10.22034/msb.2023.711490
Kashanian Monfared, N., Safaie, N., & Hosseininezhad, S. J. (2025). A decision-making model for the problem of designing the layout of medical centers considering uncertainty. System Engineering and Productivity5(2), 97-118 (In Persian). https://doi.org/10.22034/sep.2025.2049327.1252
Maghfiroh, M. F. N., & Hanaoka, S. (2020). Multi-modal relief distribution model for disaster response operations. Progress in Disaster Science, 6, 100095. https://doi.org/10.1016/j.pdisas.2020.100095
Maharjan, R., & Hanaoka, S. (2020). A credibility-based multi-objective temporary logistics hub location-allocation model for relief supply and distribution under uncertainty. Socio-Economic Planning Sciences, 70, 100727. https://doi.org/10.1016/j.seps.2019.07.003
Mamashli, Z., Bozorgi-Amiri, A., Dadashpour, I., Nayeri, S., & Heydari, J. (2021). A heuristic-based multi-choice goal programming for the stochastic sustainable-resilient routing-allocation problem in relief logistics. Neural Computing and Applications, 33(21), 14283–14309. https://doi.org/10.1007/s00521-021-06074-8
Mansoori, S., Bozorgi-Amiri, A., & Pishvaee, M. S. (2020). A robust multi-objective humanitarian relief chain network design for earthquake response, with evacuation assumption under uncertainties. Neural Computing and Applications, 32(7), 2183–2203. https://doi.org/10.1007/s00521-019-04193-x
Narimani, R., Motamedi, M., & Amoozad Khalili, H. (2023). Applying a mathematical model for the distribution of earthquake relief items to the affected areas of Tehran. Disaster Prevention and Management Knowledge, 13(2), 184–203. http://dx.doi.org/10.32598/DMKP.13.2.747.1
Ozbay, E., Çavuş, Ö., & Kara, B. Y. (2019). Shelter site location under multi-hazard scenarios. Computers & Operations Research, 106, 102–118. https://doi.org/10.1016/j.cor.2019.02.008
Peng, D., Ye, C., & Wan, M. (2022). A multi-objective improved novel discrete particle swarm optimization for emergency resource center location problem. Engineering Applications of Artificial Intelligence, 111, 104725. https://doi.org/10.1016/j.engappai.2022.104725
Pirouz, B., & Khorram, E. (2022). A computational approach based on the ε-constraint method in multi-objective optimization problems. Operations Research Forum, 3(1), 1–20. https://doi.org/10.17654/AS049060453
Praneetpholkrang, P., & Huynh, V. N. (2020). Shelter site location and allocation model for efficient response to humanitarian relief logistics. In M. Klumpp, M. Neukirchen, & M. Teuck (Eds.), Dynamics in Logistics (pp. 309–318). Springer. https://doi.org/10.1007/978-3-030-44783-0_30
Rezaei Kallaj, M., Abolghasemian, M., Moradi Pirbalouti, S., Sabk Ara, M., & Pourghader Chobar, A. (2021). Vehicle routing problem in relief supply under a crisis condition considering blood types. Mathematical Problems in Engineering, 2021, Article 7215374. https://doi.org/10.1155/2021/7217182
Roh, S.-Y., Shin, Y.-R., & Seo, Y.-J. (2018). The pre-positioned warehouse location selection for international humanitarian relief logistics. The Asian Journal of Shipping and Logistics, 34(4), 297–307. https://doi.org/10.1016/j.ajsl.2018.12.003
Sabouhi, F., Bozorgi-Amiri, A., & Vaez, P. (2020). Stochastic optimization for transportation planning in disaster relief under disruption and uncertainty. Kybernetes, 49(11), 2681–2703. https://doi.org/10.1108/K-10-2020-0632
Shao-Hong, Y., Jia-Yang, N., Tai-Long, C., Qiu-Tong, L., Cen, Y., Jia-Qing, C., & Jie, L. (2023). Location algorithm of transfer stations based on density peak and outlier detection. Applied Intelligence, 53(13), 16634–16646. https://doi.org/10.1007/s10489-022-03206-y
Temiz, S., Kazanç, H. C., Soysal, M., & Çimen, M. (2025). A probabilistic bi-objective model for a humanitarian location-routing problem under uncertain demand and road closure. International Transactions in Operational Research, 32(2), 590–625. https://doi.org/10.1111/itor.13475
Tureci-Isik, H., Çelik, M., & Sanci, E. (2025). The stochastic location-routing problem with parallel truck-drone operations for humanitarian aid delivery. European Journal of Operational Research. Advance online publication. https://doi.org/10.1016/j.ejor.2025.08.057
Wang, B., Qian, Q., Gao, J., Tan, Z., & Zhou, Y. (2021). The optimization of warehouse location and resources distribution for emergency rescue under uncertainty. Advanced Engineering Informatics, 48, 101278. https://doi.org/10.1016/j.aei.2021.101278

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انتشار آنلاین از 04 آذر 1404

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