Babaei, ArdavanKhedmati, MajidJokar, Mohammad Reza AkbariTirkolaee, Erfan Babaee2024-05-192024-05-1920230957-41741873-6793https://doi.org10.1016/j.eswa.2023.119792https://hdl.handle.net/20.500.12713/5617Transportation 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.eninfo:eu-repo/semantics/closedAccessSustainable Transportation PlanningThree-Stage Transportation ProblemTraffic CongestionData-Oriented NetworkMulti-Objective OptimizationChance-Constrained ProgrammingArticle227WOS:0010020075000012-s2.0-85152716966N/A10.1016/j.eswa.2023.119792Q1