ROUTE OPTIMIZATION OF WASTE COLLECTION VEHICLES TO THE DECENTRALIZED WASTE-TO-ENERGY POWER PLANTS - Varjonen, Essi (My University, 2018)
The increase in population and growth in economics cause the rise in living standards in developing cities. The grown living standards enable the increasing demand for services and consumer goods, which, in turn, causes the growth in municipal solid waste generation. The urbanization challenges municipalities to develop an effective and efficient municipal solid waste collecting and management system to its inhabitants. These same problems and challenges in the municipal solid waste system of developing countries also exist in Nairobi, which is the capital of the Republic of Kenya. The logistical challenge is that there is only one landfill on the other side of the city where waste has to be transported. Also, the number of vehicles is forecasted to grow in the future, which causes congestions and pollutants to the atmosphere. The purpose of the thesis was to optimize transportation routes and calculate transportation cost from the collection points to the power plants in both centralized and decentralized solutions. After that, the results of both solutions are compared to each other and cost savings in transportation are calculated with assumed values in 2018 and 2030. To find the most optimal routes, Open Door Logistics Studio, a desktop-based application for route optimizing is used. It optimizes routes with the vehicle routing problem. Monte Carlo simulation is used to calculate the distribution probability of transportation costs in 2030. The decreased annual quantity of emerged carbon footprint is also calculated because environmental prosperity is one value of the case company. The results of the study reveal that transportation costs savings depend on fuel price fluctuations. Decreased driven kilometres cause a decrease in the consumption of fuel. Thus, the fuel costs share of the total cost and the impact of fuel price fluctuations on the total cost are smaller in the decentralized solution than in the centralized solution. Transportation costs decrease by 30 % in 2018 with used input values. Savings in 2030 vary between 31 % and 38 % of the total cost with 90 % probability. The carbon footprint of transport decreases by 52 % in both 2018 and 2030. The overall conclusion from the results was that transportation costs decreased significantly in Nairobi and the cost are reasonable to investigate in other developing cities as well.
Keywords: carbon footprint; transportation cost; vehicle routing problem; fi=Tuotantotalous|en=Industrial Management|; fi=Master's Degree Programme in Industrial Management|