مکان یابی بهینه استقرار آمبولانس ها در شبکه جاده ای استان آذربایجان شرقی با رویکرد ترکیبی شبیه سازی عامل بنیان و الگوریتم ژنتیک
الموضوعات :
Bijan Elmi
1
,
Naghei Shoja
2
,
Abbass Toloie Ashlaghi
3
,
Soleyman Iranzadeh
4
1 - PhD Candidate in Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Faculty of Basic Sciences, Islamic Azad University, Firuzkuh Branch, Tehran, Iran.
3 - Professor of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
4 - Department of Industrial Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran
تاريخ الإرسال : 18 السبت , جمادى الأولى, 1442
تاريخ التأكيد : 09 الجمعة , ربيع الأول, 1443
تاريخ الإصدار : 16 الأحد , ربيع الثاني, 1443
الکلمات المفتاحية:
شبکه جاده‌ای,
استقرار,
مکانیابی,
مدلسازی عامل بنیان,
ملخص المقالة :
میزان و نوع تخصیص منابع و اتخاذ استراتژیهای لازم برای تأمین مؤثر اقدامات اورژانسی با توجه به نقش حیاتی این مراکز در سیستم سلامت، و میزان توانایی این مراکز در پاسخ مؤثر به تماسهای اورژانسی یک عنصر مهم در تأمین و بازیابی سلامت بیماران محسوب میشود. بهینه‌ترین موقعیت مکانی اورژانسها با توجه به کنش متقابل بین عوامل، محدودیتهای محیطی و ویژگیهای رفتاری متفاوت عوامل مختلف مفروض در مسئله را بیابیم. از لحاظ هدف کاربردی و توصیفی با رویکرد مدلسازی تبیینی که در ارائه مدل از نظرسنجی خبرگان استفاده و در اجرای مدل که مبتنی بر کاربست الگوریتم متاهیورستیکال (از نوع ژنتیک) میباشد، دادههای عینی و ذهنی ترکیب گردیده متغیرهای عامل و محیطی طی رویکرد ترکیبی شبیه‌سازی عامل بنیان و الگوریتم متاهیورستیک مدلیزه شده‌اند. زمان اولیه برای پیمایش یک ساختار اولیه برای ۴۰ نقطه حادثه‌خیز و ۵ ایستگاه برابر با 7860 بوده که پس از بهینه‌سازی به روش ژنتیک و تولید لیست جدید و نیز جهش آمبولانسها از یک ایستگاه به ایستگاه دیگر نتایج به عددی بین 2700 الی 4000 رسید. استفاده از این نوع بهینه‌سازی میتواند به‌سرعت فعالیتها و کاهش هزینه‌ها کمک شایانی نماید. با توجه به یکسان نبودن ترافیک نقاط، زمان رسیدن آمبولانس به نقاط حادثه‌خیز برابر نخواهد بود لذا با تغییر نقاط استقرار، بنا بر شرایط با جلو یا عقب رفتن و اختصاصی نمودن خصوصیات آمبولانسها و نقاط حادثه‌خیز و ترکیب لیست نقاط میتوان زمان پیمایش کل نقاط حادثه‌خیز را کاهش داد.
المصادر:
Aringhieri, R., Bruni, M. E., Khodaparasti, S., & van Essen, J. (2017). Emergency medical services and beyond: Addressing new challenges through a wide literature review. Computers & Operations Research, 48 (1): 22-23.
Bafandeh Zendeh, A., & Danaye Nemat Abad, N. (2016). A Factor-based model for analyzing consumer preference for goods. Intrnational Conference on Industrial Engineering and Management, Tehran, Permanent Secretariat of the Conference, 2 (1): 38-47.
Basar, A., Catay, B., &¨Unl¨uyurt, T. (2011). A multi-period double coverage approach for locating the emergency medical service stations in Istanbul. Journal of the Operational Research Society, 62 (12): 627–637.
Batta, R., Dolan, J. , & Krishnamurty, N. N. (1998). The maximal expected covering location problem: Revisited. Transportation Science, 23 (3): 277–287.
Beraldi, P., Bruni, M. , & Conforti, D. (2004). Designing robust emergency medical service via stochastic programming. European Journal of Operational Research, 158 (2): 183–193.
Beraldi, P. , & Bruni, M. (2009). A probabilistic model applied to emergency service vehicle location. European Journal of Operational Research, 196 (2): 323–331.
Cassco, (2001). Fuzzy thinking ،Mashhad Khajeh Nasir al-Din Tusi University, Press Second Edition, 17 (58), 310-317.
Chanta, S., Mayorga, M. , Kurz, M. E., & McLay, L. A. (2011). The minimum p-envy locationproblem: a new model for equitable distribution of emergency resources. IIE Transactions on Healthcare Systems Engineering, 1 (3): 101–115.
Church, R. , & ReVelle, C. S. (1974). The maximal covering location problem. Papers of Regional Science Association, 32 (2): 101–118.
Daskin, M. , & Stern, E. H. (1981). A hierarchical objective set covering model for emergency medical service vehicle deployment.Transportation Science 15 (4): 137–152.
Gendreau, M., Laporte, G., & Semet, F. (1997). Solving an ambulance location model by tabu search. Location Science 5 (1): 75–88.
J., Dietrich. R., Chen, J. M., Mitwasi, M. G., Valenzuela, T. , & Criss, E. (1990). Validating and applying a model for locating emergency medical services in Tucson, AZ. European Journal of Operational Research, 49 (2): 308–324.
Hogan, K., & ReVelle, C. (1986). Concepts and application of backup coverage. Management Science, 34 (3): 1434–1444.
Litkoohi, S., Jahan Bakhsh, , & CHarkh CHian, M. (2014). Booklet of Location theories, Payame Noor University Press, 12 (71): 101-110.
Macal, C., & Sallach, M. (2010). North, eds., Chicago, IL, Oct. 7-9, available at, (pp. 185-204).
Merrikh Bayat, F. (2014). Metaheuristic Optimization algorithms (with application in electrical engineering). Jihad Daneshgahi Publications, 67 (2): 91-98.
McLay, L. , & Mayorga, M. E. (2013b). A dispatching model for server-to-customer systems that balances efficiency and equity. Manufacturing & Service Operations Management, 15 (2): 205–220.
McLay, L. A., & Mayorga, M. E. (2013c). A model for optimally dispatching ambulances to emergency calls with classification errors in patient priorities. IIE Transactions, 45 (2): 1–24.
Marianov, V., & ReVelle, C. (1994). The queuing probabilistic location set covering problem and some extensions. Socio-Economic Planning Sciences, 28 (1): 167–178.
Marianov, V., & ReVelle, C. (1995). Siting emergency services. In: Drezner, Z. (Ed.), Facility Location. A survey of Applications and Methods. Springer, New York, N. Y., (pp. 119–223).
Marianov, V., & ReVelle, C. (1996). The queuing maximal availability location problem: A model for the siting of emergency vehicles. European Journal of Operational Research, 93 (3): 110–120.
Mason, A. (2013). Simulation and real-time optimised relocation for improving ambulance operations. In: Denton, B. (Ed.), Handbook of Healthcare Operations: Methods and Applications. Springer, New York, N. Y., (pp. 289–317).
Nickel, S., Reuter-Oppermann, M., & da Gama, F. (2016). Ambulance location under stochastic demand: A sampling approach. Operations Research for Health Care, 8 (2): 24–32.
Rajagopalan, H. , Saydam, C., & Xiao, J. (2008). A multiperiod set covering location model for dynamic redeployment of ambulances. Computers & Operations Research, 35 (4): 814–826.
Repede, J. , & Bernardo, J. J. (1994). Developping and validating a decision support system for location emergency medical vehicles in Louisville, Kentucky. European Journal of Operational Research, 75 (2): 567–581.
Reuter-Oppermann, M., van den Berg, P. , & Vile, J. L. (2017). Logistics for emergency medical, Journal Health Systems, Volume 6, Issue 3, 187-208.
ReVelle, C. , & Hogan, K. (1988). A reliability constrained siting model with local estimates of busy fractions. Environment and Planning B, 15 (2): 143–152.
ReVelle, C. , & Hogan, K. (1989). The maximum availability location problem. Transportation Science 23, 192–200.
Su, Q., Luo, Q., & Huang, H. (2015). Cost-effective analyses for emergency medical services deployment: A case study in shanghai. International Journal of Production Economics, 163 (12): 112–123.
Tahan, M. (2015). Emergency center Location model on city roads, Mashhad Ferdowsi University, 17 (54): 112-119.
Toregas, C., Swain, R., ReVelle, C. , & Bergman, L. (1971). The location of emergency service facilities. Operations Research, 19 (12): 1363–1373.
Zhang, Z. H., & Li, K. (2015). A novel probabilistic formulation for locating and sizing emergency medical service stations. Annals of Operations Research, 229 (6): 813–835
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Aringhieri, R., Bruni, M. E., Khodaparasti, S., & van Essen, J. (2017). Emergency medical services and beyond: Addressing new challenges through a wide literature review. Computers & Operations Research, 48 (1): 22-23.
Bafandeh Zendeh, A., & Danaye Nemat Abad, N. (2016). A Factor-based model for analyzing consumer preference for goods. Intrnational Conference on Industrial Engineering and Management, Tehran, Permanent Secretariat of the Conference, 2 (1): 38-47.
Basar, A., Catay, B., &¨Unl¨uyurt, T. (2011). A multi-period double coverage approach for locating the emergency medical service stations in Istanbul. Journal of the Operational Research Society, 62 (12): 627–637.
Batta, R., Dolan, J. , & Krishnamurty, N. N. (1998). The maximal expected covering location problem: Revisited. Transportation Science, 23 (3): 277–287.
Beraldi, P., Bruni, M. , & Conforti, D. (2004). Designing robust emergency medical service via stochastic programming. European Journal of Operational Research, 158 (2): 183–193.
Beraldi, P. , & Bruni, M. (2009). A probabilistic model applied to emergency service vehicle location. European Journal of Operational Research, 196 (2): 323–331.
Cassco, (2001). Fuzzy thinking ،Mashhad Khajeh Nasir al-Din Tusi University, Press Second Edition, 17 (58), 310-317.
Chanta, S., Mayorga, M. , Kurz, M. E., & McLay, L. A. (2011). The minimum p-envy locationproblem: a new model for equitable distribution of emergency resources. IIE Transactions on Healthcare Systems Engineering, 1 (3): 101–115.
Church, R. , & ReVelle, C. S. (1974). The maximal covering location problem. Papers of Regional Science Association, 32 (2): 101–118.
Daskin, M. , & Stern, E. H. (1981). A hierarchical objective set covering model for emergency medical service vehicle deployment.Transportation Science 15 (4): 137–152.
Gendreau, M., Laporte, G., & Semet, F. (1997). Solving an ambulance location model by tabu search. Location Science 5 (1): 75–88.
J., Dietrich. R., Chen, J. M., Mitwasi, M. G., Valenzuela, T. , & Criss, E. (1990). Validating and applying a model for locating emergency medical services in Tucson, AZ. European Journal of Operational Research, 49 (2): 308–324.
Hogan, K., & ReVelle, C. (1986). Concepts and application of backup coverage. Management Science, 34 (3): 1434–1444.
Litkoohi, S., Jahan Bakhsh, , & CHarkh CHian, M. (2014). Booklet of Location theories, Payame Noor University Press, 12 (71): 101-110.
Macal, C., & Sallach, M. (2010). North, eds., Chicago, IL, Oct. 7-9, available at, (pp. 185-204).
Merrikh Bayat, F. (2014). Metaheuristic Optimization algorithms (with application in electrical engineering). Jihad Daneshgahi Publications, 67 (2): 91-98.
McLay, L. , & Mayorga, M. E. (2013b). A dispatching model for server-to-customer systems that balances efficiency and equity. Manufacturing & Service Operations Management, 15 (2): 205–220.
McLay, L. A., & Mayorga, M. E. (2013c). A model for optimally dispatching ambulances to emergency calls with classification errors in patient priorities. IIE Transactions, 45 (2): 1–24.
Marianov, V., & ReVelle, C. (1994). The queuing probabilistic location set covering problem and some extensions. Socio-Economic Planning Sciences, 28 (1): 167–178.
Marianov, V., & ReVelle, C. (1995). Siting emergency services. In: Drezner, Z. (Ed.), Facility Location. A survey of Applications and Methods. Springer, New York, N. Y., (pp. 119–223).
Marianov, V., & ReVelle, C. (1996). The queuing maximal availability location problem: A model for the siting of emergency vehicles. European Journal of Operational Research, 93 (3): 110–120.
Mason, A. (2013). Simulation and real-time optimised relocation for improving ambulance operations. In: Denton, B. (Ed.), Handbook of Healthcare Operations: Methods and Applications. Springer, New York, N. Y., (pp. 289–317).
Nickel, S., Reuter-Oppermann, M., & da Gama, F. (2016). Ambulance location under stochastic demand: A sampling approach. Operations Research for Health Care, 8 (2): 24–32.
Rajagopalan, H. , Saydam, C., & Xiao, J. (2008). A multiperiod set covering location model for dynamic redeployment of ambulances. Computers & Operations Research, 35 (4): 814–826.
Repede, J. , & Bernardo, J. J. (1994). Developping and validating a decision support system for location emergency medical vehicles in Louisville, Kentucky. European Journal of Operational Research, 75 (2): 567–581.
Reuter-Oppermann, M., van den Berg, P. , & Vile, J. L. (2017). Logistics for emergency medical, Journal Health Systems, Volume 6, Issue 3, 187-208.
ReVelle, C. , & Hogan, K. (1988). A reliability constrained siting model with local estimates of busy fractions. Environment and Planning B, 15 (2): 143–152.
ReVelle, C. , & Hogan, K. (1989). The maximum availability location problem. Transportation Science 23, 192–200.
Su, Q., Luo, Q., & Huang, H. (2015). Cost-effective analyses for emergency medical services deployment: A case study in shanghai. International Journal of Production Economics, 163 (12): 112–123.
Tahan, M. (2015). Emergency center Location model on city roads, Mashhad Ferdowsi University, 17 (54): 112-119.
Toregas, C., Swain, R., ReVelle, C. , & Bergman, L. (1971). The location of emergency service facilities. Operations Research, 19 (12): 1363–1373.
Zhang, Z. H., & Li, K. (2015). A novel probabilistic formulation for locating and sizing emergency medical service stations. Annals of Operations Research, 229 (6): 813–835
