نوع مقاله : مقاله پژوهشی

نویسنده

استادیار دانشگاه آزاد اسلامی ، واحد قزوین، دانشکده مهندسی صنایع و مکانیک، گروه مهندسی صنایع، قزوین

چکیده

در این تحقیق یک مدل برنامه ریزی مختلط عدد صحیح چند هدفه به منظور طراحی یک شبکه خدمات درمانی
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برای نزدیک تر شدن مدل به واقعیت، با استفاده از رویکرد بهینه سازی استوار، مدل در حالت غیرقطعی نیز
گسترش یافته است. تابع هدف مورد اول، هزینه های مرتبط با حمل ونقل، استریلیزاسیون و همچنین جابجایی
منابع را کمینه می نماید. تابع هدف دوم، حداقل سطح سرویس دهی مراکز خدمات درمانی به مشتریان را
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طوریکه دارای انحراف استاندارد بسیار پایین تری نسبت به مدل قطعی می باشد.

کلیدواژه‌ها

عنوان مقاله [English]

Designing and Solving Multi-Objective Optimization Model for Healthcare Networks with Risk Pooling Effect Under Uncertainty: Robust Optimization Method

نویسنده [English]

  • Behnam Vahdani

چکیده [English]

In this research, a multi-objective mixed integer programming model is presented to design a healthcare network with risk pooling effect. Since the model parameters have also uncertainty, for closing the model to reality, using robust optimization approach, the model is also extended in a state of uncertainty. Objective functions that have been used, include minimization of transportation costs, costs related to sterilization, as well as the movement of resources. We are also looking for maximizing the minimum level of service provision of healthcare centers to customers. Also, for solving the proposed model, we utilized a multi-objective fuzzy method which is developed in recent years. Moreover, several numerical examples are brought up to show the accuracy and validity of the model. The results obtained from this analysis, showed the accuracy of behavior of the model and the proposed approach in different modes. Computational results show that the robust model provides more high-quality solutions, in a way that it has far less standard deviation compared to deterministic model

کلیدواژه‌ها [English]

  • Healthcare network design
  • Multi-Objective Optimization
  • robust optimization
  • risk pooling
  • Location-Allocation
Ahmed, S. J., (2004). 'Improving access to public health care services- a case study on Dar es Salaam, Tanzania', International Institute for Geo Information Science and Earth Observation, MSc thesis.
Aptel, O., Pourjalali, H., (2001). Improving activities and decreasing costs of logistics in hospitals: a comparison for US and French hospitals, The International Journal of Accounting 36, Pages 65–90.
Ben-Tal, A., El-Ghaoui, L., Nemirovsky, A., )2009(. Robust Optimization. Princeton University Press, Princeton, NJ.
Chen, M.S., Lin, C.T., (1989). Effects of centralization on expected costs in a multi-location newsboy problem. Journal of Operations Research Society 40 (6), 597–602.
Chu, S.C.K., Chu, L., (2000). A modelling framework for hospital location and service allocation, International Transactions in Operational Research 7, Pages 359–368.
Daskin, M. S., & Coullard, C. R., (2002). An inventory–location model?: Formulation, solution algorithm and computational results. Annals of Operations Research, 110, 83–106.
Daskin, M. S., Dean, L. K., (2004), 'A Handbook of OR/MS in Health Care: Health Care Facilities', Northwestern University.
Drezner, T., Drezner, Z., (2007). 'The gravity p-median model', European Journal of Operational Research, 179, Pages 1239-1251.
Friesz, T. L., Lee, I., & Lin, C. C., (2011). Competition and disruption in a dynamic urban supply chain. Transportation Research Part B: Methodological,45(8), 1212-1231.

Hovav, S., & Tsadikovich, D., (2015). A network flow model for inventory management and distribution of influenza vaccines through a healthcare supply chain. Operations Research for Health Care, 5, 49-62.
Lai, Y. J., & Hwang, C. L., (1993). Possibilistic linear programming for managing interest rate risk. Fuzzy Sets and Systems, 54(2), 135-146.
Lega, F., (2005).Strategies for multi-hospital networks: a framework, Health Services Management Research 18, Pages 86–99.
Mestre, A. M., Oliveira, M. D., & Barbosa-Póvoa, A. P., (2015). Location–allocation approaches for hospital network planning under uncertainty.European Journal of Operational Research, 240(3), 791-806.
Miranda, P. A., & Garrido, R. A. (2004)., Incorporating inventory control decisions into a strategic distribution network design model with stochastic demand. Transportation Research Part E: Logistics and Transportation Review,40(3), 183-207.
Mohammadi, M., Dehbari, S., & Vahdani, B., (2014). Design of a bi-objective reliable healthcare network with finite capacity queue under service covering uncertainty. Transportation Research Part E: Logistics and Transportation Review, 72, 15-41.
Niakan, F., & Rahimi, M., (2015). A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach. Transportation Research Part E: Logistics and Transportation Review, 80, 74-94.
Pasin, F., Jobin, M.H., Cordeau, J.F., (2001).Application d’une approche de simulation pour analyser le partage de ressources entre des organisations du secteur de la santé, Cahier de recherche n◦ 01–02, HEC Montréal.

Peterson, R., & Silver, E. A., (1979). Decision systems for inventory management and production planning (pp. 799-799). New York: Wiley.
Rahman, S., Smith, D. K., (1999). Deployment of rural health facilities in a developing country. Journal of the Operational Research Society (50), 892–902.
Rahman, S., Smith, D., (2000).Use of location–allocation models in health service development planning in developing nations, European Journal of Operational Research 123, Pages 437–452.
Sakawa, M., Yano, H., & Yumine, T., (1987). An interactive fuzzy satisficing method for multiobjective linear-programming problems and its application.Systems, Man and Cybernetics, IEEE Transactions on, 17(4), 654-661.
Selim, H., & Ozkarahan, I., (2008). A supply chain distribution network design model: an interactive fuzzy goal programming-based solution approach. The International Journal of Advanced Manufacturing Technology, 36(3-4), 401-418.
Shariff, S. R., Moin, N. H., & Omar, M., (2012). Location allocation modeling for healthcare facility planning in Malaysia. Computers & Industrial Engineering, 62(4), 1000-1010.
Syam, S. S., & Côté, M. J., (2012). A comprehensive location-allocation method for specialized healthcare services. Operations Research for Health Care, 1(4), 73-83.
Tlahig, H., Bouchriha, H., Jebali, A., Ladet, P., (2008).A mathematical model for the internalization/ externalization decision of the hospital sterilization process, in: Post-Conference Proceedings of the 33rd International Conference on Operational Research Applied to Health Services, -ORAHS’07.

Tlahig, H., Jebali, A., Bouchriha, H., (2009).A two-phased approach for the centralization vs. decentralization of the hospital sterilization department, European Journal of Industrial Engineering 3 (2), Pages 227–246.
Tlahig, H., Jebali, A., Bouchriha, H., Ladet, P., (2013). Centralized versus distributed sterilization service: A location–allocation decision model, Operations Research for Health Care, 2(4), Pages 75-85.
Torabi, S., Hassini, E., (2008) "An interactive possibilistic programming approach for multiple objective supply chain master planning," Fuzzy Sets and Systems, vol. 159, Pages 193-214.
Werners, B. M., (1988). Aggregation models in mathematical programming. InMathematical models for decision support (pp. 295-305). Springer Berlin Heidelberg.
Zahiri, B., Tavakkoli-Moghaddam, R., & Pishvaee, M. S., (2014). A robust possibilistic programming approach to multi-period location–allocation of organ transplant centers under uncertainty. Computers & Industrial Engineering, 74, 139-148.
Zimmermann, H. J., (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy sets and systems, 1(1), 45-55