Integrating electric vehicles in a supply chain and distribution is a viable option when special conditions such as short distance road distribution and environmental considerations as well as small amounts of goods enabling delivery with delivery vans are met. In this paper, possibility of investment in electric vehicles for distribution of local food will be examined and analysed. Safety concerns in electric vehicles will also be addressed and accident consequences and vehicle safety will be analysed and compared with conventional vehicles that use internal combustion engines.
This paper presents the review of policies and their possible effects for promoting the use of electric vehicles. Suggestions on faster implementation of electric vehicles can also be identified within best practices from abroad. Various countries have adopted different policies to promote the use of electric vehicles which include fiscal or other forms of incentives that would persuade people into buying electric vehicles. Possible effects are hard to determine since many variables affect a consumer’s purchasing decisions. That is why identification of policies that have proven to be successful and those that have not achieved projected results and should be improved is necessary. Research has shown that countries with most promising policies for promotion have the biggest share of electric vehicles and invest the most in their promotion (fiscal incentives).
In 2015 the Agenda 2030 was introduced, framed of 17 sustainable development goals (SDG) with 169 targets, which were adopted by the United Nations Member States and should bring prosperity and growth to the global society. In this paper a focus is given to the SDG 12 Sustainable consumption and production from the e-mobility perspective. SDG 12 aims to ensure sustainable consumption and production (SCP) patterns – it is about promoting resource and energy efficiency, sustainable infrastructure, and providing access to basic services, green and decent jobs, and a better quality of life for all. Many stakeholders from public and private sector are investing a lot of effort to identify consumer behaviour for future improvements in development of their green products and strategies Because sustainable mobility and consequently low emission vehicles (LEV) are closely related with sustainable consumption within the personal mobility this paper focuses on consumer segmentation of potential LEV buyers and their willingness to buy LEV. Results have revealed that the segment of potential alternative fuel vehicles buyers is much larger than we initially anticipated. Such vehicles are, surprisingly, also more attractive for the older population, according to our results.
Distribution is one of the major sources of carbon emissions and this issue has been addressed by Green Vehicle Routing Problem (GVRP). This problem aims to fulfill the demand of a set of customers using a homogeneous fleet of Alternative Fuel Vehicles (AFV) originating from a single depot. The problem also includes a set of Alternative Fuel Stations (AFS) that can serve the AFVs. Since AFVs started to operate very recently, Alternative Fuel Stations servicing them are very few. Therefore, the driving span of the AFVs is very limited. This makes the routing decisions of AFVs more difficult. In this study, we formulated a multi-objective optimization model of Green Vehicle Routing Problem with two conflicting objective functions. While the first objective of our GVRP formulation aims to minimize total CO2 emission, which is proportional to the distance, the second aims to minimize the maximum traveling time of all routes. To solve this multi-objective problem, we used ɛ-constraint method, a multi-objective optimization technique, and found the Pareto optimal solutions. The problem is formulated as a Mixed-Integer Linear Programming (MILP) model in IBM OPL CPLEX. To test our proposed method, we generated two hypothetical but realistic distribution cases in Izmir, Turkey. The first case study focuses on an inner-city distribution in Izmir, and the second case study involves a regional distribution in the Aegean Region of Turkey. We presented the Pareto optimal solutions and showed that there is a tradeoff between the maximum distribution time and carbon emissions. The results showed that routes become shorter, the number of generated routes (and therefore, vehicles) increases and vehicles visit a lower number of fuel stations as the maximum traveling time decreases. We also showed that as maximum traveling time decreases, the solution time significantly decreases.
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