The identification and ranking of the indicators affecting the routing and scheduling of sustainable urban transportation using multi-criteria decisions

Subject Areas : Industrial Management

shiba masoumi ¹ , Seyyed Mohammad Hadji Molana ² , Mehrdad Javadi ³ , Amir Azizi ⁴

1 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3 - Associated Professor, Department of Mechanical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.
4 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

Received: 2021-04-15 Accepted : 2022-05-01 Published : 2022-06-08

Keywords: Ranking, Keywords: Multi-criteria decision making, Scheduling, Sustainable urban transportation, routing,

Abstract :

AbstractThe present study was carried out in order to evaluate and rank the indicators of urban transport sustainability using descriptive-analytical methodology and Delphi methods, best-worst and best priority. In order to achieve the indicators of sustainable transportation in three economic, social and environmental dimensions, the criteria were ranked based on library studies, and the opinion of experts, so as to finalize the criteria of great importance on the research issue to enter the Delphi method, and be used as the evaluation criteria to save time and the number of trips. The final criteria were entered into the weighting and ranking process using the best-worst method and the best priority method. The results of the two methods of best-worst and best priority were compared using statistical methods.Considering that the ranking of the criteria was the same in both methods and the Spearman correlation coefficient was +1, so there is a strong correlation between the criteria.Also, the Pearson correlation coefficient between weights was 0.989 and the significance level was zero, which demonstrate a strong relationship between variables. Therefore, ranking and weighting obtained from the two methods were accepted.

References:

1. Abdullahi, H., Reyes-Rubiano, L., Ouelhadj, D., Faulin, J., & Juan, A. A. (2021). Modelling and multi-criteria analysis of the sustainability dimensions for the green vehicle routing problem. European Journal of Operational Research, 292(1), 143-154.


2. Aboutalebi Esfahani, M., Haghshenas, H., & Mohammadhoseini, M. (2018). Assessing the impact of inland freight transport on sustainable transport indicators (Case study: Ahwaz city). Quarterly Journal of Transportation Engineering, (In persian)


3. Alonso, A., Monzón, A., & Cascajo, R. (2015). Comparative analysis of passenger transport sustainability in European cities. Ecological Indicators, 48, 578-592.


4. Amanpour, S., Nemati, M., & Alizadeh, H. (2014). Assessment and Priority Surveying of Urban Transport Sustainability Indicators Using Fuzzy Logic (Case in Ahvaz). Geographical Space, 4(47), 213-231. (In persian)


5. Asgharizadeh, E., Jafar Nejad, A., Zandieh, M., & Jooybar, S. (2017). Explaining the Approach of Traffic Modeling to Vehicle Routing Issues Based on the Paradigm of Green Transportation (Case Study: ZAMZAM Co). Journal of Industrial Management, 9(2), 217 - 244. (In persian)


6. Asgharpour, M. J. (2008). Multi-criteria decision making. Tehran: Tehran University Publications. (In persian)


7. Ataei, Y., Mahmoudi, A., Feylizadeh, M. R., & Li, D.-F. (2020). Ordinal Priority Approach (OPA) in Multiple Attribute Decision-Making. Applied Soft Computing, 86, 105893.


8. Baharum, S., Haron, S., Ishak, S. Z., & Mansor, S. (2019). Sustainable Urban Bus Service Assessment and Tourists’ Satisfaction. J Sup. Chain. Mgt Vol, 8(3), 570.


9. Batchelor, T., & Briffa, M. (2011). Fight tactics in wood ants: Individuals in smaller groups fight harder but die faster. Biological sciences / The Royal Society, 278, 3243-3250.


10. Cheng, C., Yang, P., Qi, M., & Rousseau, L.-M. (2017). Modeling a green inventory routing problem with a heterogeneous fleet. Transportation Research Part E: Logistics and Transportation Review, 97, 97-112.


11. Cottam, H.-R., Roe, M., & Challacombe, J. (2004). Outsourcing of trucking activities by relief organisations.


12. Dündar, H., Ömürgönülşen, M., & Soysal, M. (2020). A review on sustainable urban vehicle routing. Journal of Cleaner Production, 125444.


13. Eskandarpour, M., Ouelhadj, D., & Fletcher, G. (2019). Decision making using metaheuristic optimization methods in sustainable transportation. Sustainable Transportation and Smart Logistics, 285-304.


14. Ezzati Arasteh Pour, F., Sohrabi, R., Samadi, A., & Rahbar, A. H. (2018). The Achievement of Sustainable Transport Future Using Scenario Planning (Case Study: Urban Transportation of Hamedan). Journal of Transportation Research, 15(3), 205-222. (In persian)


15. Gibbons, J. D., & Chakraborti, S. (2011). Nonparametric Statistical Inference. In M. Lovric (Ed.), International Encyclopedia of Statistical Science (pp. 977-979). Berlin, Heidelberg: Springer Berlin Heidelberg.


16. Guzman, L. A., de la Hoz, D., & Monzón, A. (2014). Optimal and Long-Term Dynamic Transport Policy Design: Seeking Maximum Social Welfare through a Pricing Scheme. International Journal of Sustainable Transportation, 8(4), 297-316.


17. Haghshenas, H., & Vaziri, M. (2012). Urban sustainable transportation indicators for global comparison. Ecological Indicators, 15(1), 115-121.


18. Jahanshahloo, L., & Amini, E. (2006). Urban planning and its role in achieving sustainable urban transportation. Paper presented at the 7th International Conference on Transportation and Traffic Engineering. (In persian)


19. Jeon, C. M., Amekudzi, A. A., & Guensler, R. L. (2013). Sustainability assessment at the transportation planning level: Performance measures and indexes. Transport Policy, 25, 10-21.


20. Majidi, S., Hosseini-Motlagh, S.-M., & Ignatius, J. (2018). Adaptive large neighborhood search heuristic for pollution-routing problem with simultaneous pickup and delivery. Soft Computing, 22(9), 2851-2865.


21. Mehdinia, I., Mehdinia, M., & Shirazian, G. (2015). Provide a method for assessing the sustainability of transportation in the social dimension. Paper presented at the 14th International Conference on Transportation and Traffic Engineering. (In persian)


22. Mirzaaghaei, M., Hadipour, M., & Rahmani, M. (2015). Presenting effective environmental factors and indicators in sustainable urban transportation (Case study: Qom city). Paper presented at the 14th International Conference on Transportation and Traffic Engineering. (In persian)


23. Mirzabaghi, M., Jolai, F., Razmi, J., & Tavakkoli-Moghaddam, r. (2021). Sustainable routing of heterogeneous vehicles with simultaneous pickup and delivery considering economic, environmental and social factors. Journal of Transportation Research, 18(1), 227-250. (In persian)


24. Mohammadi Dah Cheshmeh, P., & Mahdavi, D. (2019). Strategic planning for improvement of Shahrekord Transportation system placement by using a combination approaches of SWOT and QSPM. Geography and Planning, 23(68), 245-264. (In persian)


25. Mostafazadeh, M., & Jafari, A. (2014). Provide a multi-objective mathematical model for the design of a sustainable supply chain network taking into account inventory management. Paper presented at the 14th International Conference on Transportation and Traffic Engineering. (In persian)


26. Nejadirani, F., & Zati, S. (2017). Evaluation of sustainable and healthy city indicators with emphasis on urban transportation management strategies by AHP method; Case study of Urmia. Paper presented at the International Conference on Civil Engineering, Architecture and Urban Planning of Contemporary Iran. (In persian)


27. Piran, H. R., Saeedeh Zarabadi, Z. S., Ziari, Y., & Majedi, H. (2019). Explaining sustainable urban transport indicators using structural equations (Case study: Tehran Metro lines 1 and 2). Geography (Regional Planning), 9(2), 521-538. (In persian)


28. Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2014). An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain. Transportation Research Part E: Logistics and Transportation Review, 67, 14-38.


29. Raju, K. S., & Kumar, D. N. (1999). Multicriterion decision making in irrigation planning. Agricultural Systems, 62(2), 117-129.


30. Rassafi, A., & Vaziri, M. (2005). Sustainable transport indicators: definition and integration. International Journal of Environmental Science & Technology, 2(1), 83-96.


31. Reisi, M., Aye, L., Rajabifard, A., & Ngo, T. (2014). Transport sustainability index: Melbourne case study. Ecological Indicators, 43, 288–296.


32. Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 3, 49-57.


33. Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130.


34. Shiau, T.-A., & Liu, J.-S. (2013). Developing an indicator system for local governments to evaluate transport sustainability strategies. Ecological Indicators, 34, 361-371.


35. Suryani, E., Hendrawan, R., Adipraja, P., & Indraswari, R. (2020). System dynamics simulation model for urban transportation planning: a case study. International Journal of Simulation Modelling, 19(1), 5-16.


36. Tian, Z., Zhong, R. Y., Vatankhah Barenji, A., Wang, Y., Li, Z., & Rong, Y. (2021). A blockchain-based evaluation approach for customer delivery satisfaction in sustainable urban logistics. International Journal of Production Research, 59(7), 2229-2249. (In persian)


37. Yousefinavid, M., Rahmani, A., & Ghorbankhani, M. (2015). Evaluation and prioritization of sustainable transportation implementation strategies in the metropolis of Hamadan with the approach of sustainable urban development. Paper presented at the 14th International Conference on Transportation and Traffic Engineering.


38. Zito, P., & Salvo, G. (2011). Toward an urban transport sustainability index: An European comparison. European Transport Research Review, 3.