نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی صنایع، دانشگاه روزبهان، ساری، ایران.

2 گروه مهندسی صنایع، موسسه آموزش عالی آیندگان، تنکابن، ایران.

چکیده

بحران‌ ﺣﺎﺩﺛﻪﺍﻯ ﺍﺳﺖ ﻛﻪ به‌طور طبیعی ﻳﺎ ﺑﻪ‌وسیله‌ی ﺑﺸﺮ، به‌طور ﻧﺎﮔﻬﺎنی ﻳﺎ ﺑﻪ‌ﺻﻮﺭت فزاﻳﻨﺪﻩ ﺑﻪ‌ﻭﺟﻮﺩ میﺁﻳﺪ و ﺑﺮﺍی برطرف‌کردن ﺁﻥ ﻧﻴﺎﺯ ﺑﻪ اقدامات ﺍﺿﻄﺮﺍﺭی و ﺍﺳﺎسی می‌باﺷﺪ. هنگامی که بحران اتفاق می‌افتد مکان انبارهای ازقبل تعیین ‌شده، نقش مهمی در امداد‌‌رسانی خواهد ‌داشت، بنابراین انتخاب محل‌های مناسب برای انبارها یکی از اهداف اصلی ما در این پژوهش می‌باشد. در این پژوهش، یک مدل دوهدفه‌ی برنامه‌ریزی خطی برای مرحله‌ی آماده‌سازی مدیریت بحران با استفاده از زیرساخت‌های شهری استفاده می‌شود تا با‌توجه به محدودیت‌های موجود و اهداف حداقل‌کردن، حداکثر وزن مکان‌ها (مینیماکس وزن مکان‌ها) و حداقل‌کردن هزینه‌ها با درنظر گرفتن حداکثر فواصل مجاز با مکان‌های آسیب دیده و جاده‌های اصلی و بیمارستان‌های مجهز پس‌از وقوع حادثه، بتوان مسئله‌ی مکان‌یابی را حل کرد. بدین منظور از روش‌های دقیق همچون روش مجموع وزنی، روش برنامه‌ریزی آرمانی و LPمتریک استفاده شده است که درنهایت بهترین مکان‌های بالقوه با کم‌ترین هزینه‌ها انتخاب می‌گردد که این نتایج به سازمان‌های بحران، کمک زیادی خواهد کرد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Multi-location logistics in relief with regard to urban infrastructure

نویسندگان [English]

  • Reza Hasan Zadeh 1
  • Shirin Alizade 2

1 Department of Industrial Engineering, Rouzbahan University, Sari, Iran.

2 Department of Industrial Engineering, Ayandegan Institute of Higher Education, Tonekabon, Iran.

چکیده [English]

Crises are the inevitable realities of human life; which is an accident that occurs naturally or suddenly or increasingly by human and to address it, there is a need for urgent and fundamental measures.When the crisis occurs, pre-determined storage locations will play an important role in relief; therefore, the selection of suitable places for warehouses is one of our main goals in this research. In this research, a bi-objective linear programing model with integer variables is developed. The proposed model attempt to minimize total cost along with maximizing the minimum weight of open shelter areas while deciding on the location of shelter areas, the assigned population points to each open shelter area and controls the utilization of open shelter areas. In order to solve proposed model, some of well-known multi-objective, exact methods includes a weighted sum method, LP-metric method, and goal programing approach are employed.Finally, the best open shelter areas with considering the minimum cost is obtained, which these results can be useful for crisis organizations.

کلیدواژه‌ها [English]

  • Relief logistic
  • Location Allocation
  • Multi-objective optimization
Chang, M. S., Tseng, Y. L., & Chen, J. W. (2007). A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transportation research part E: logistics and transportation review, 43(6), 737-754.
Altay, N., & Green Iii, W. G.  (2006 ). OR/MS research in disaster operations management.  Eur. J. Oper. Res., 175(1), 475–493.
Bozorgi-Amiri, A., Jabalameli, M. S., & Al-e-Hashem, S. M. (2013). A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty. OR spectrum, 35(4), 905-933.
Jabbarzadeh, A., Fahimnia, B., & Seuring, S. (2014). Dynamic supply chain network design for the supply of blood in disasters: a robust model with real world application. Transportation research part E: logistics and transportation review, 70, 225-244.
Afshar, A., & Haghani, A. (2012). Modeling integrated supply chain logistics in real-time large-scale disaster relief operations. Socio-economic planning sciences, 46(4), 327-338.
Campbell, A. M., & Jones, P. C. (2011). Prepositioning supplies in preparation for disasters. European journal of operational research, 209(2), 156-165.
Alçada‐Almeida, L., Tralhao, L., Santos, L., & Coutinho‐Rodrigues, J. (2009). A multiobjective approach to locate emergency shelters and identify evacuation routes in urban areas. Geographical analysis, 41(1), 9-29.
Jia, H., Ordóñez, F., & Dessouky, M. M. (2007). Solution approaches for facility location of medical supplies for large-scale emergencies. Computers & industrial engineering, 52(2), 257-276.
Garrido, R. A., Lamas, P., & Pino, F. J. (2015). A stochastic programming approach for floods emergency logistics. Transportation research part E: logistics and transportation review, 75, 18-31.
Najafi, M., Eshghi, K., & Dullaert, W. (2013). A multi-objective robust optimization model for logistics planning in the earthquake response phase. Transportation research part E: logistics and transportation review, 49(1), 217-249.
Dessouky, M., Ordóñez, F., Jia, H., & Shen, Z. (2013). Rapid distribution of medical supplies. In Patient flow (pp. 385-410). Springer, Boston, MA.
Haowei, Z., Junwei, X., Jiaang, G., Wenlong, L. & Binfeng Z. (2018). An entropy-based PSO for DAR task scheduling problem. Applied soft computing, 73, 862-873.
Akbari, M., &Rashidi, H. (2016). A multi-objectives scheduling algorithm based on Cuckoo optimization for task allocation problem at compile time in heterogeneous systems. Expert systems with applications, 60, 234–248.
Oh, G., Kim, Y., Ahn, J., & Choi, H. L. (2016). PSO-based optimal task allocation for cooperative timing missions. IFAC-PapersOnLine49(17), 314-319.
Kılcı, F., Kara, B. Y., & Bozkaya, B. (2015). Locating temporary shelter areas after an earthquake: A case for Turkey. European journal of operational research, 243(1), 323-332.
Pasandideh, S. H. R., Niaki, S. T. A., & Asadi, K. (2015). Optimizing a bi-objective multi-product multi-period three echelon supply chain network with warehouse reliability. Expert systems with applications, 42(5), 2615-2623.