Đánh giá an toàn đường bộ và phân prioritization rủi ro sử dụng phương pháp tích hợp SWARA và MARCOS trong môi trường mờ cầu đối

Saeid Jafarzadeh Ghoushchi1, Sina Shaffiee Haghshenas2, Ali Memarpour Ghiaci1, Giuseppe Guido2, Alessandro Vitale2
1Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran
2Department of Civil Engineering, University of Calabria, Via Bucci, 87036, Rende, Italy

Tóm tắt

Tóm tắtCó rất nhiều yếu tố làm cho việc đánh giá an toàn đường bộ trở nên không thể đoán trước và khó hiểu. Điều này có thể gây nguy hiểm đến tính mạng con người, ảnh hưởng đến sức khỏe tâm thần của xã hội và dẫn đến những tổn thất tài chính và nhân đạo kéo dài. Do sự mập mờ và không chắc chắn trong quá trình đánh giá rủi ro, một kỹ thuật quyết định đa tiêu chí nhằm xử lý các hệ thống phức tạp, liên quan đến việc chọn một trong nhiều tùy chọn, là một chiến lược quan trọng trong việc đánh giá an toàn đường bộ. Trong nghiên cứu này, một phương pháp phân tích tỷ lệ trọng số từng bước (SWARA) tích hợp với đo lường các lựa chọn và xếp hạng theo giải pháp thỏa hiệp (MARCOS) dưới một tập hợp mờ cầu đối (SF) đã được xem xét. Sau đó, phương pháp được đề xuất đã được áp dụng để phát triển phương pháp phân tích chế độ hỏng và tác động (FMEA) cho các con đường nông thôn ở Cosenza, miền Nam Italy. Ngoài ra, các kết quả của FMEA đã được điều chỉnh bằng SF-SWARA-MARCOS đã được so sánh với các kết quả của FMEA truyền thống. Các kết quả điểm số rủi ro cho thấy rằng nguồn gốc của rủi ro (con người) đóng một vai trò quan trọng trong các vụ tai nạn so với các nguồn rủi ro khác. Hai rủi ro, bao gồm sạt lở đất và lũ lụt, có giá trị thấp nhất trong số các yếu tố ảnh hưởng đến an toàn đường bộ nông thôn ở Calabria, tương ứng. Sự tương quan giữa các kết quả kịch bản và các thứ tự xếp hạng chính trong các giá trị trọng số cũng đã được điều tra. Nghiên cứu này được thực hiện phù hợp với các mục tiêu phát triển bền vững và mục tiêu di chuyển bền vững, nhằm tìm ra rủi ro và giảm thiểu số vụ tai nạn trên đường. Do đó, điều quan trọng là phải xem xét lại các luật lệ và biện pháp cần thiết để giảm thiểu rủi ro từ con người trên mạng lưới đường bộ khu vực Calabria nhằm cải thiện an toàn đường bộ.

Từ khóa


Tài liệu tham khảo

Stamatis DH (2003) Failure mode and effect analysis: FMEA from theory to execution. Quality Press, Welshpool, WA

Shi H et al (2020) A novel method for failure mode and effects analysis using fuzzy evidential reasoning and fuzzy Petri nets. J Ambient Intell Humaniz Comput 11(6):2381–2395

Li X-Y et al (2019) Failure mode and effect analysis using interval type-2 fuzzy sets and fuzzy Petri nets. J Intell Fuzzy Syst 37(1):693–709

Shahri MM, Jahromi AE, Houshmand M (2021) Failure Mode and Effect Analysis using an integrated approach of clustering and MCDM under pythagorean fuzzy environment. J Loss Prev Process Ind 72:104591

Jafarzadeh Ghoushchi S et al (2020) Integrated decision-making approach based on SWARA and GRA methods for the prioritization of failures in solar panel systems under Z-information. Symmetry 12(2):310

Liu H-C et al (2019) Failure mode and effect analysis using multi-criteria decision making methods: a systematic literature review. Comput Ind Eng 135:881–897

Di Bona G et al (2018) Total efficient risk priority number (TERPN): a new method for risk assessment. J Risk Res 21(11):1384–1408

Park J, Park C, Ahn S (2018) Assessment of structural risks using the fuzzy weighted Euclidean FMEA and block diagram analysis. Int J Adv Manuf Technol 99(9):2071–2080

Liu H-C, Liu L, Liu N (2013) Risk evaluation approaches in failure mode and effects analysis: a literature review. Expert Syst Appl 40(2):828–838

Gul M, Ak MF (2021) A modified failure modes and effects analysis using interval-valued spherical fuzzy extension of TOPSIS method: case study in a marble manufacturing facility. Soft Comput 25(8):6157–6178

Jafarzadeh Ghoushchi S et al (2022) Barriers to circular economy implementation in designing of sustainable medical waste management systems using a new extended decision-making and FMEA models. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-022-19018-z

Lotfi Z (1965) Fuzzy sets. Inf Control 8(3):338–353

Ghoushchi SJ et al (2021) An extended new approach for forecasting short-term wind power using modified fuzzy wavelet neural network: a case study in wind power plant. Energy 223:120052

Hosseini SM, Paydar MM, Hajiaghaei-Keshteli M (2021) Recovery solutions for ecotourism centers during the Covid-19 pandemic: utilizing fuzzy DEMATEL and fuzzy VIKOR methods. Expert Syst Appl 185:115594

Ghoushchi SJ et al (2021) Landfill site selection for medical waste using an integrated SWARA-WASPAS framework based on spherical fuzzy set. Sustainability 13(24):13950

Kutlu Gündoğdu F, Kahraman C (2019) A novel VIKOR method using spherical fuzzy sets and its application to warehouse site selection. J Intell Fuzzy Syst 37(1):1197–1211

Gündoğdu FK, Kahraman C (2020) A novel spherical fuzzy QFD method and its application to the linear delta robot technology development. Eng Appl Artif Intell 87:103348

Ashraf S, Abdullah S, Mahmood T (2020) Spherical fuzzy Dombi aggregation operators and their application in group decision making problems. J Ambient Intell Humaniz Comput 11(7):2731–2749

Kutlu Gundogdu F, Kahraman C (2019) Extension of WASPAS with spherical fuzzy sets. Informatica 30(2):269–292

Boltürk E (2019) AS/RS technology selection using spherical fuzzy TOPSIS and neutrosophic TOPSIS. In: International conference on intelligent and fuzzy systems. Springer

Cox JA, Beanland V, Filtness AJ (2017) Risk and safety perception on urban and rural roads: effects of environmental features, driver age and risk sensitivity. Traffic Inj Prev 18(7):703–710

Guido G et al (2020) Development of a binary classification model to assess safety in transportation systems using GMDH-type neural network algorithm. Sustainability 12(17):6735

Xie S et al (2020) Exploring risk factors with crash severity on China two-lane rural roads using a random-parameter ordered probit model. J Adv Transp 2020:1–14

Sheykhfard A et al (2020) Structural equation modelling of potential risk factors for pedestrian accidents in rural and urban roads. Int J Inj Control Saf Promot 28(1):46–57

Huang J et al (2020) Failure mode and effect analysis improvement: a systematic literature review and future research agenda. Reliab Eng Syst Saf 199:106885

Amini A, Mojtaba F (2018) Risk assessment of Namaklan road tunnel using Failure Mode and Effect Analysis (FMEA). In: Tunnelling and climate change conference

Javadieh N, Abdekhodaee A, Ektesabi MM (2014) Risk analysis of human errors in road transport using H-FMEA technique. In: Transport Research Arena (TRA) 5th conference: transport solutions from research to deployment European Commission conference of European Directors of Roads (CEDR) European Road Transport Research Advisory Council (ERTRAC) WATERBORNETP European Rail Research Advisory Council (ERRAC) Institut Francais des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR) Ministère de l'Écologie, du Développement Durable et de l'Énergie

Lo H-W et al (2020) A hybrid MCDM-based FMEA model for identification of critical failure modes in manufacturing. Soft Comput 24(20):15733–15745

Boral S, Chakraborty S (2021) Failure analysis of CNC machines due to human errors: an integrated IT2F-MCDM-based FMEA approach. Eng Fail Anal 130:105768

Alvand A et al (2021) Identification and assessment of risk in construction projects using the integrated FMEA-SWARA-WASPAS model under fuzzy environment: a case study of a construction project in Iran. In: International journal of construction management, pp 1–23

Ghoushchi SJ, Yousefi S, Khazaeili M (2019) An extended FMEA approach based on the Z-MOORA and fuzzy BWM for prioritization of failures. Appl Soft Comput 81:105505

Keršuliene V, Zavadskas EK, Turskis Z (2010) Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). J Bus Econ Manag 11(2):243–258

Keršulienė V, Turskis Z (2011) Integrated fuzzy multiple criteria decision making model for architect selection. Technol Econ Dev Econ 17(4):645–666

Zolfani SH, Saparauskas J (2013) New application of SWARA method in prioritizing sustainability assessment indicators of energy system. Eng Econ 24(5):408–414

Alimardani M et al (2013) A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technol Econ Dev Econ 19(3):533–548

Stanujkic D, Karabasevic D, Zavadskas EK (2015) A framework for the selection of a packaging design based on the SWARA method. Eng Econ 26(2):181–187

Aghdaie MH, Zolfani SH, Zavadskas EK (2013) Decision making in machine tool selection: an integrated approach with SWARA and COPRAS-G methods. Eng Econ 24(1):5–17

Prajapati H, Kant R, Shankar R (2019) Prioritizing the solutions of reverse logistics implementation to mitigate its barriers: a hybrid modified SWARA and WASPAS approach. J Clean Prod 240:118219

Karabašević D et al (2016) An approach to personnel selection based on SWARA and WASPAS methods. Bizinfo (Blace) J Econ Manag Inform 7(1):1–11

Heidary Dahooie J et al (2018) Competency-based IT personnel selection using a hybrid SWARA and ARAS-G methodology. Hum Factors Ergon Manuf Serv Ind 28(1):5–16

Hashemkhani Zolfani S, Bahrami M (2014) Investment prioritizing in high tech industries based on SWARA-COPRAS approach. Technol Econ Dev Econ 20(3):534–553

Vojinović N, Stević Ž, Tanackov I (2022) A novel IMF SWARA-FDWGA-PESTEL analysis for assessment of healthcare system. Oper Res Eng Sci: Theory Appl 5(1):139–151

Yücenur GN, Ipekçi A (2021) SWARA/WASPAS methods for a marine current energy plant location selection problem. Renew Energy 163:1287–1298

Dursun M, Karsak EE (2010) A fuzzy MCDM approach for personnel selection. Expert Syst Appl 37(6):4324–4330

Bozanic D, Tešić D, Milić A (2020) Multicriteria decision making model with Z-numbers based on FUCOM and MABAC model. Decis Mak: Appl Manag Eng 3(2):19–36

Zarbakhshnia N, Soleimani H, Ghaderi H (2018) Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria. Appl Soft Comput 65:307–319

Ghoushchi SJ et al (2022) Evaluation of wind turbine failure modes using the developed SWARA-CoCoSo methods based on the spherical fuzzy environment. IEEE Access 10:86750–86764

Rani P et al (2020) Pythagorean fuzzy SWARA–VIKOR framework for performance evaluation of solar panel selection. Sustainability 12(10):4278

Ghoushchi SJ et al (2021) Risk prioritization in failure mode and effects analysis with extended SWARA and MOORA methods based on Z-numbers theory. Informatica 32(1):41–67

He J et al (2021) Developing a new framework for conceptualizing the emerging sustainable community-based tourism using an extended interval-valued Pythagorean fuzzy SWARA-MULTIMOORA. Technol Forecast Soc Chang 171:120955

Rahmati S et al (2022) Assessment and prioritize risk factors of financial measurement of management control system for production companies using a hybrid Z-SWARA and Z-WASPAS with FMEA method: a meta-analysis. Mathematics 10(2):253

Stević Ž et al (2020) Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Comput Ind Eng 140:106231

Stević Ž, Brković N (2020) A novel integrated FUCOM-MARCOS model for evaluation of human resources in a transport company. Logistics 4(1):4

Ecer F (2021) A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies. Renew Sustain Energy Rev 143:110916

Chakraborty S, Chattopadhyay R, Chakraborty S (2020) An integrated D-MARCOS method for supplier selection in an iron and steel industry. Decis Mak: Appl Manag Eng 3(2):49–69

Bakır M, Akan Ş, Özdemir E (2021) Regional aircraft selection with fuzzy piprecia and fuzzy marcos: a case study of the Turkish airline industry. Facta Univ Ser: Mech Eng 19(3):423–445

Madić M, Petrović G (2016) Application of the ORESTE method for solving decision making problems in transportation and logistics. UPB Sci Bull Ser D: Mech Eng 78(4):83–94

Stanković M et al (2020) A new fuzzy MARCOS method for road traffic risk analysis. Mathematics 8(3):457

Bakır M, Atalık Ö (2021) Application of fuzzy AHP and fuzzy MARCOS approach for the evaluation of e-service quality in the airline industry. Decis Mak: Appl Manag Eng 4(1):127–152

Ecer F, Pamucar D (2021) MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services. Appl Soft Comput 104:107199

Kutlu Gündoğdu F, Kahraman C (2019) Spherical fuzzy sets and spherical fuzzy TOPSIS method. J Intell Fuzzy Syst 36(1):337–352

Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning—I. Inf Sci 8(3):199–249

Kiracı K, Akan E (2020) Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets. J Air Transp Manag 89:101924

Atanassov K (1988) Review and new results on intuitionistic fuzzy sets. Preprint Im-MFAIS-1-88, Sofia 5(1)

Yager RR (2013) Pythagorean fuzzy subsets. In: 2013 joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS). IEEE

Ashraf S et al (2019) Different approaches to multi-criteria group decision making problems for picture fuzzy environment. Bull Braz Math Soc New Ser 50(2):373–397

Kutlu Gündoğdu F, Kahraman C (2020) A novel spherical fuzzy analytic hierarchy process and its renewable energy application. Soft Comput 24(6):4607–4621

Gündoğdu FK, Kahraman C (2019) Extension of WASPAS with spherical fuzzy sets

Wong SC et al (2004) A qualitative assessment methodology for road safety policy strategies. Accid Anal Prev 36(2):281–293

Siliquini R et al (2010) A European study on alcohol and drug use among young drivers: the TEND by Night study design and methodology. BMC Public Health 10(1):1–6

Guido G et al (2020) Feasibility of stochastic models for evaluation of potential factors for safety: a case study in Southern Italy. Sustainability 12(18):7541

Amiri AM, Nadimi N, Yousefian A (2020) Comparing the efficiency of different computation intelligence techniques in predicting accident frequency. IATSS Res 44(4):285–292

Rahman R, Hasan S, Zaki MH (2021) Towards reducing the number of crashes during hurricane evacuation: assessing the potential safety impact of adaptive cruise control systems. Transp Res Part C: Emerg Technol 128:103188

Fu C, Sayed T, Zheng L (2021) Multi-type Bayesian hierarchical modeling of traffic conflict extremes for crash estimation. Accid Anal Prev 160:106309

Guido G et al (2022) Evaluation of contributing factors affecting number of vehicles involved in crashes using machine learning techniques in rural roads of Cosenza, Italy. Safety 8(2):28

Fu C, Sayed T (2022) Bayesian dynamic extreme value modeling for conflict-based real-time safety analysis. Anal Methods Accid Res 34:100204

BURC (2016) n. 123 del 27 Dicembre 2016, Piano Regionale dei Trasporti, Regione Calabria

ISTAT (2021) Focus incidenti stradali Calabria 2020

Toker K, Görener A (2022) Evaluation of circular economy business models for SMEs using spherical fuzzy TOPSIS: an application from a developing countries’ perspective. Environ Dev Sustain. https://doi.org/10.1007/s10668-022-02119-7

Akram M, Kahraman C, Zahid K (2021) Group decision-making based on complex spherical fuzzy VIKOR approach. Knowl-Based Syst 216:106793

Kovač M et al (2021) Novel spherical fuzzy MARCOS method for assessment of drone-based city logistics concepts. Complexity 2021:1–17

Rolison JJ et al (2018) What are the factors that contribute to road accidents? An assessment of law enforcement views, ordinary drivers’ opinions, and road accident records. Accid Anal Prev 115:11–24

Shinar D (2007) Traffic safety and human behavior. Elsevier, Amsterdam

WHO (2018) Global Status Report on Safety 2018. World Health Organization, SUI, Geneva

NHTSA (2021) Traffic Safety Facts 2019. U.S Department of Transportation, Washington, DC