Sustainable transportation planning considering traffic congestion and uncertain conditions

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dc.authoridTirkolaee, Erfan Babaee/0000-0003-1664-9210
dc.authoridKhedmati, Majid/0000-0001-8803-0658
dc.authorwosidTirkolaee, Erfan Babaee/U-3676-2017
dc.contributor.authorBabaei, Ardavan
dc.contributor.authorKhedmati, Majid
dc.contributor.authorJokar, Mohammad Reza Akbari
dc.contributor.authorTirkolaee, Erfan Babaee
dc.date.accessioned2024-05-19T14:46:55Z
dc.date.available2024-05-19T14:46:55Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractTransportation activities, especially road transportation, have a great impact on economic growth. On the other hand, sustainability is a major concern for transportation planning. In this work, a data-oriented network is developed to evaluate the sustainability of vehicle types. Then, this network is integrated with a multi-objective optimization model in order to provide the planning of a three-stage transportation problem, according to traffic congestion. Some criteria including total profit, efficiency of different vehicle types, relationship among the customers supplied by a specified retailer, risk of underestimating unmet demand, and selling price are used to determine the objective functions. The Chance-Constrained Programming (CCP) and Chebyshev Goal Pro-gramming (CGP) approaches are applied to solve the proposed integrated model. To the best of the authors' knowledge, it is the first time that traffic congestion under the conditions of simultaneous fuzzy and stochastic uncertainty has been integrated into sustainable transportation planning. In addition, the applicability and validity of the developed model are assessed on a case study. The results are then analyzed and appraised by Data Envelopment Analysis (DEA) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The findings prove that the components of the proposed model have a very beneficial effect on the solution, and also perform much better than the competing approaches in the literature. Two important points from the results of this paper are that (a) traffic congestion is more effective in the initial levels of the supply chain, and (b) transportation planning using efficient vehicles may reduce the desirability of the objective function values.en_US
dc.identifier.doi10.1016/j.eswa.2023.119792
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.scopus2-s2.0-85152716966en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org10.1016/j.eswa.2023.119792
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5617
dc.identifier.volume227en_US
dc.identifier.wosWOS:001002007500001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectSustainable Transportation Planningen_US
dc.subjectThree-Stage Transportation Problemen_US
dc.subjectTraffic Congestionen_US
dc.subjectData-Oriented Networken_US
dc.subjectMulti-Objective Optimizationen_US
dc.subjectChance-Constrained Programmingen_US
dc.titleSustainable transportation planning considering traffic congestion and uncertain conditionsen_US
dc.typeArticleen_US

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