مدلسازی و حل مسئله‌ی تصادفی پوشش حداکثری تسهیلات پیشگیرانه‌ی متعدد با الگوریتم‌های فراابتکاری

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه مهندسی صنایع، واحد بناب، دانشگاه آزاد اسلامی، بناب، ایران

چکیده

پژوهش حاضر در مورد مکان‌یابی تسهیلات پیشگیرانه می‌باشد. خدمات موثّر مراقبت‌های بهداشتی پیشگیرانه، نقش مهمی در کاهش هزینه‌های پزشکی و مرگ و میر در همه‌ی جوامع انسانی دارند و سطح دسترسی مشتریان به این خدمات می‌تواند به عنوان مقیاس کارآیی و تاثیرشان بررسی شود. برای اینکه مشکل انتظار و صف حل شود یک مساله‌ی دوهدفه‌ی ریاضی و غیرخطی ارائه شده تا موضوع کاهش حداکثر زمان انتظار مراجعه کنندگان با هدف افزایش حداکثر مقدار پوشش‌دهی بررسی گردد. روش تحقیق پژوهش حاضر از نوع مدلسازی ریاضی است. تجزیه و تحلیل اطلاعات با استفاده از نرم‌فزار Matlab انجام شده و جواب‌های بدست آمده از الگوریتم‌های متاهیورستیک در نرم‌افزار Minitab مقایسه شده است. از نتایج این تحقیق، می توان به افزایش پوشش توسط تسهیلات پیشگیرانه و افزایش زمان انتظار اشاره نمود. از دیگر نتایج این تحقیق، مقایسه‌ی کارایی هر یک از الگوریتم‌های فرا ابتکاری NSGAII و MOIWO نسبت به شاخص‌های تعریف شده می‌باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Modeling and Solving the Stochastic Problem of Maximum Coverage of Multi-Preventive Facilities with Meta-Heuristic Algorithms 

نویسندگان [English]

  • Zohreh , Khalilpour
  • Mahdi Yousefi Nezhad Attari
 Department of Islamic Azad University of Bonab Branch, Bonab, Iran 
چکیده [English]

 The present research is about the location of preventive facilities. Effective preventive health care services play an important role in reducing medical costs and mortality in all human societies, and the level of customer access to these services can be considered as a measure of their effectiveness and effectiveness. In order to solve the waiting and queuing problem, a biobjective mathematical and nonlinear problem is presented to address the issue of reducing the maximum waiting time for the visitors with the aim of increasing the maximum coverage. This research method is based on modeling. Data analysis was performed using Matlab software, and the answers obtained from the meta-heuristic algorithms were compared in the Minitab software. From the results of this study, it is possible to increase coverage by preventive facilities and increase waiting time. Another result of this study is the comparison of the effectiveness of each of the metaheuristic NSGAII and MOIWO with the defined index. 
 
 

کلیدواژه‌ها [English]

  • Preventive facility location
  • Multi-objective optimization model
  • Queuing theory
  • Meta- heuristics. 

 

[1]         K. Walker, “Current issues in the provision of health care services,” J. Consum. Aff., vol. 11, no. 2, pp. 52–62, 1977.
[2]         W. H. Organization, P. H. A. of Canada, and C. P. H. A. of Canada, Preventing chronic diseases: a vital investment. World Health Organization, 2005.
[3]         M. E. Gornick, P. W. Eggers, and G. F. Riley, “Associations of race, education, and patterns of preventive service use with stage of cancer at time of diagnosis,” Health Serv. Res., vol. 39, no. 5, pp. 1403–1428, 2004.
[4]         W. H. Organization and others, “Integrating prevention into health care. Fact sheet 172,” 2010.
[5]         S. Javanmardi, H. Hosseininasab, and A. Mostafaeipour, “An exact Method for Stochastic Maximal Covering Problem of Preventive Healthcare Facilities,” J. Ind. Syst. Eng., vol. 10, no. special issue on healthcare, pp. 10–23, Mar. 2017.
[6]         R. Church and C. ReVelle, “The maximal covering location problem,” in Papers of the Regional Science Association, 1974, vol. 32, no. 1, pp. 101–118.
 
[7]         J. E. Weiss, M. R. Greenlick, and J. F. Jones, “Determinants of medical care utilization: the impact of spatial factors,” Inquiry, vol. 8, no. 4, pp. 50–57, 1971.
[8]         O. Berman, “The maximizing market size discretionary facility location problem with congestion,” Socioecon. Plann. Sci., vol. 29, no. 1, pp. 39–46, 1995.
[9]         B. Adenso-Diaz and F. Rodriguez, “A simple search heuristic for the MCLP: Application to the location of ambulance bases in a rural region,” Omega, vol. 25, no. 2, pp. 181–187, 1997.
[10]       V. Verter and S. D. Lapierre, “Location of Preventive Health Care Facilities,” Ann. Oper. Res., vol. 110, no. 1, pp. 123–132, 2002.
[11]       V. Marianov, “Location of multiple-server congestible facilities for maximizing expected demand, when services are non-essential,” Ann. Oper. Res., vol. 123, no. 1–4, pp. 125–141, 2003.
[12]       V. R. Ghezavati, M. S. Jabal-Ameli, and A. Makui, “A new heuristic method for distribution networks considering service level constraint and coverage radius,” Expert Syst. Appl., vol. 36, no. 3, pp. 5620–5629, Apr. 2009.
[13]       Y. Zhang, O. Berman, and V. Verter, “Incorporating congestion in preventive healthcare facility network design,” Eur. J. Oper. Res., vol. 198, no. 3, pp. 922–935, 2009.
[14]       Y. Zhang, O. Berman, P. Marcotte, and V. Verter, “A bilevel model for preventive healthcare facility network design with congestion,” IIE Trans., vol. 42, no. 12, pp. 865–880, 2010.
 
[15]       A. Ceder, “Optimal Multi-Vehicle Type Transit Timetabling and Vehicle Scheduling,” Procedia - Soc. Behav. Sci., vol. 20, pp. 19–30, 2011.
[16]       T. Kozasa, M. Tsukai, and A. Fujiwara, “A Development of Dynamic Road Network Planning Model Considering Step-by-step Construction of Links and Facility on Nodes,” Procedia - Soc. Behav. Sci., vol. 43, pp. 384–398, 2012.
[17]       A. Redmer, J. Żak, P. Sawicki, and M. Maciejewski, “Heuristic approach to fleet composition problem,” Procedia-Social Behav. Sci., vol. 54, pp. 414–427, 2012.
[18]       Y. Zhang, O. Berman, and V. Verter, “Incorporating congestion in preventive healthcare facility network design,” Eur. J. Oper. Res., vol. 198, no. 3, pp. 922–935, Nov. 2009.
[19]       S. Javanmardi, H. Hosseininasab, and A. Mostafaeipour, “An exact Method for Stochastic Maximal Covering Problem of Preventive Healthcare Facilities,” vol. 10, pp. 10–23, 2017.
[20]       Y. Zhang, O. Berman, and V. Verter, “The impact of client choice on preventive healthcare facility network design,” OR Spectr., vol. 34, no. 2, pp. 349–370, 2012.
[21]       H. Maghsoudlou, B. Afshar-Nadjafi, and S. T. A. Niaki, “Multi-skilled project scheduling with level-dependent rework risk; three multi-objective mechanisms based on cuckoo search,” Appl. Soft Comput., vol. 54, pp. 46–61, 2017.