The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the alternative locations. The intersection of three different suitability indexes is determined so as to achieve a holistic, credible result. While the two different weights for each criterion are obtained by means of AHP in terms of environmental impact and accessibility, another weight for each criterion is obtained as a means of applying the FAHP.

In this regard, the Analytic Hierarchy Process (AHP) and the Fuzzy Analytic Hierarchy Process (FAHP) methods are used to calculate the weights of criteria.

In this sense, the aim of this paper is to propose an approach that integrates Geographic Information System (GIS) techniques and Multi-Criteria Decision Making (MCDM) methods for finding suitable locations of the electric vehicle charging stations. The location selection of electric vehicle charging stations is one of the most vital topics in order to enhance the use of electric vehicles. Furthermore, this tool provides a means to calculate the present fuel costs, emission of CO2 for each bus line, and the estimated electricity costs.Įlectric vehicles arouse interest since they not only contribute economies of countries in the context of dependency to oil but also support to more livable and sustainable urban areas. Its application is feasible in any city since it requires as input data: the technical characteristics of electric and combustion buses, operational details of existing routes, and the number of passengers per route. The methodology is suitable for aiding municipalities in identifying adequate bus lines to start this shift. The economic savings reach 83% with respect the diesel consumption. The replacement to EBs of the three best-performing bus lines (50 buses) avoids using 1328 gallons of diesel each day and, thereby, over 13.3 metric tons of CO2 and other polluting gases into the atmosphere. The results indicate that the proposed methodology enables the establishment of route prioritization for the transition toward electric mobility. The case study of Cuenca, Ecuador, which is an intermediate Andean city, is considered. The scores of each criterion are weighted using a multi-criteria technique. This paper proposes a new methodology to address the transition of urban public transportation from conventional buses to EBs by route prioritization. However, the transition from internal combustion engine buses to electric buses (EBs) is accompanied by new challenges for the power grid, particularly in developed countries. This is particularly so in the case of vehicles for public transportation, such as buses. The factors that most influence decision making are the number of passengers served, the length of the trip and the energy required by the route.Įlectric vehicles have attracted increasing interest in recent years owing to their reduced environmental impact. Given 23 lines and 475 bus units, the method enabled us to determine that in an initial phase, 68 electric buses are required to be used on five lines to reduce fuel consumption. After the values defining each criterion and its corresponding weight were processed, the final ranking makes it possible to prioritize one route before others. A final rank of routes is obtained using Visual PROMETHEE software. The Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) multicriteria technique is used to detect the best routes according to technical, social, environmental, economic and location criteria. This work establishes a methodological process with a set of tools to prioritize the gradual migration from conventional to electric buses according to the characteristics of each route. Because the relevant costs include those associated with replacing equipment and improving route networks, alternatives that prioritize incorporating the first units on the best routes are being sought. Ecuadorian legislation has specified gradually replacing traditional public bus transport units with electric units. In Cuenca, Ecuador, fossil fuels for transportation represent 59.9% of total energy consumption. Transportation consumes approximately 29% of the world's energy and is responsible for approximately 25% of CO 2 emissions worldwide.

Routing slip masstransit