Assessment of Fuzzification Effect of AHP and TOPSIS in Site Selection of Roadside EMS Stations

سال انتشار: 1398
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 176

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شناسه ملی سند علمی:

JR_JORAR-11-2_006

تاریخ نمایه سازی: 23 بهمن 1399

چکیده مقاله:

: In order to prevent and reduce the death and disability rates caused by road accidents, it is necessary to optimize the location of the roadside emergency medical service (EMS) stations. Optimal selection of the EMS stations is a multi-criteria decision-making (MCDM) problem and usually involves the analysis of a large number of possible options and evaluation criteria. Nowadays, various MCDM methods are used to solve location problems that may generate different results. The fuzzification of these methods has always been one of the controversial issues with many agreements and disagreements. METHODS: In this study, a review was first performed on the weighting methods including five non-fuzzy weighting methods as row sum, column sum, arithmetic mean, geometric mean, and eigenvalues as well as two fuzzy weighting methods including: “Liu and Chen method” and “Chang Method”. Then, the fuzzy and non-fuzzy MCDM methods [including analytic hierarchy process (AHP), fuzzy analytic hierarchy process (FAHP) Chang, FAHP Liu, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and fuzzy TOPSIS (FTOPSIS)] were employed to locate the roadside EMS stations. Due to insufficient information and all the required layers in Iran, the information of the Interstate-65 (I-65) Highway between Montgomery and Birmingham, Alabama, USA was used in the present study. Finally, the results of these methods were compared using the mean-score, Borda, and Copeland prioritization strategies. FINDINGS: Given the importance and sensitivity of the issue, a combination of the MCDM methods was utilized to locate the EMS stations and the most appropriate non-fuzzy and fuzzy weighting methods were identified and the methods used were compared in terms of complexity, volume and time of computations, and the level of impact of the expert opinion. CONCLUSION: The AHP, FAHP Liu and Chen, FAHP Chang, and TOPSIS methods yielded more reliable results in locating the roadside EMS stations, in addition, using FTOPSIS fuzzy method was more risky and is not recommended. The non-fuzzy AHP method was identified to be the most reliable method in the present study.

کلیدواژه ها:

: Emergency Medical Service Location ، Multi-Criteria Decision-Making ، Prioritization Strategy ، Roadside Emergency Medical Service ، : Emergency Medical Service Location ، Multi-Criteria Decision-Making ، Prioritization Strategy ، Roadside Emergency Medical Service

نویسندگان

Ali Mansour-Khaki

Faculty Member, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

Barat Mojarradi

Faculty Member, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

Behrouz Ghobadipour

School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

Soroush Maghsoud

Department of Mineral Environment, School of Mining Engineering, University of Tehran, Tehran, Iran

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  • Mollaghasemi M, Pet-Edwards J. Making multi-objective decisions. Washington, DC: IEEE ...
  • Toloie-Eshlaghy A, Homayonfar M. MCDM methodologies and applications: A literature ...
  • Vinodh S, Prasanna M, Hari Prakash N. Integrated fuzzy AHPTOPSIS ...
  • Nguyen HT, Dawal SZM, Nukman Y, Aoyama H. A hybrid ...
  • Ghassemi SA, Danesh S. A hybrid fuzzy multi-criteria decision making ...
  • Tavana M, Khalili-Damghani K, Abtahi AR. A hybrid fuzzy group ...
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  • Wu CM, Hsieh CL, Chang KL. A hybrid multiple criteria ...
  • Kabak M, Burmaoglu S, Kazancoglu Yi. A fuzzy hybrid MCDM ...
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  • Wang F, Kang S, Du T, Li F, Qiu R. ...
  • Shelton J, Medina M. Integrated multiple-criteria decision-making method to prioritize ...
  • Rossetti MD, Selandari F. Multi-objective analysis of hospital delivery systems. ...
  • Singpurwalla N, Forman E, Zalkind D. Promoting shared health care ...
  • Vahidnia MH, Alesheikh AA, Alimohammadi A. Hospital site selection using ...
  • Khaki AM, Mojaradi B, Ghobadipour B, Maghsoudi S, Naghibi F. ...
  • Daskin MS, Stern EH. A hierarchical objective set covering model ...
  • Doerner KF, Gutjahr WJ, Hartl RF, Karall M. Heuristic solution ...
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  • Van Laarhoven PJM, Pedrycz W. A fuzzy extension of Saaty's ...
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  • Bonacich P. Factoring and weighting approaches to status scores and ...
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  • Ramik J, Korviny P. Inconsistency of pair-wise comparison matrix with ...
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  • National Highway Traffic Safety Administration. Fatality Analysis Reporting System (FARS) ...
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  • 1. Mollaghasemi M, Pet-Edwards J. Making multi-objective decisions. Washington, DC: IEEE ...
  • 2. Toloie-Eshlaghy A, Homayonfar M. MCDM methodologies and applications: A literature ...
  • 3. Vinodh S, Prasanna M, Hari Prakash N. Integrated fuzzy AHPTOPSIS ...
  • 4. Nguyen HT, Dawal SZM, Nukman Y, Aoyama H. A hybrid ...
  • 5. Ghassemi SA, Danesh S. A hybrid fuzzy multi-criteria decision making ...
  • 6. Tavana M, Khalili-Damghani K, Abtahi AR. A hybrid fuzzy group ...
  • 7. Sakthivel G, Ilangkumaran M, Nagarajan G, Shanmugam P. Selection of ...
  • 8. Kasirian MN, Yusuff RM. An integration of a hybrid modified ...
  • 9. Wu CM, Hsieh CL, Chang KL. A hybrid multiple criteria ...
  • 10. Kabak M, Burmaoglu S, Kazancoglu Yi. A fuzzy hybrid MCDM ...
  • 11. Alcan P, Balin A, Basligil H. Fuzzy multicriteria selection among ...
  • 12. Mahdavi A, Niknejad M. Site suitability evaluation for ecotourism using ...
  • 13. Wang F, Kang S, Du T, Li F, Qiu R. ...
  • 14. Shelton J, Medina M. Integrated multiple-criteria decision-making method to prioritize ...
  • 15. Rossetti MD, Selandari F. Multi-objective analysis of hospital delivery systems. ...
  • 16. Singpurwalla N, Forman E, Zalkind D. Promoting shared health care ...
  • 17. Vahidnia MH, Alesheikh AA, Alimohammadi A. Hospital site selection using ...
  • 18. Khaki AM, Mojaradi B, Ghobadipour B, Maghsoudi S, Naghibi F. ...
  • 19. Daskin MS, Stern EH. A hierarchical objective set covering model ...
  • 20. Doerner KF, Gutjahr WJ, Hartl RF, Karall M. Heuristic solution ...
  • 21. Saaty TL. The analytic hierarchy process: Planning, priority setting, resource ...
  • 22. Boroushaki S, Malczewski J. Implementing an extension of the analytical ...
  • 23. Saaty TL. The analytic hierarchy process: Planning, priority setting, resource ...
  • 24. Saaty TL, Tran LT. On the invalidity of fuzzifying numerical ...
  • 25. Zadeh LA. Fuzzy sets. Inf Control 1965; 8(3): 338-53. ...
  • 26. Zadeh LA. Fuzzy sets as a basis for a theory ...
  • 27. Rahman MA, Rusteberg B, Gogu RC, Lobo Ferreira JP, Sauter ...
  • 28. Van Laarhoven PJM, Pedrycz W. A fuzzy extension of Saaty's ...
  • 29. Chang DY. Applications of the extent analysis method on fuzzy ...
  • 649-55. ...
  • 30. Liu YC, Chen CS. A new approach for application of ...
  • 129-43. ...
  • 31. Hwang CL, Yoon K. Multiple attribute decision making: Methods and ...
  • 32. Saaty TL. How to make a decision: The analytic hierarchy ...
  • 33. Forman E, Peniwati K. Aggregating individual judgments and priorities with ...
  • 34. Bonacich P. Factoring and weighting approaches to status scores and ...
  • 35. Hwang CL, Yoon K. Multiple attribute decision making: Methods and ...
  • 36. Ramik J, Korviny P. Inconsistency of pair-wise comparison matrix with ...
  • 37. Zhu K. Fuzzy analytic hierarchy process: Fallacy of the popular ...
  • 38. National Highway Traffic Safety Administration. Fatality Analysis Reporting System (FARS) ...
  • 39. Homer C, Huang C, Yang L, Wylie B, Coan M. ...
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