Public Transportation Energy Planning by Network Analysis-A Case Study of Kathmandu Valley

This paper is an attempt to find out the required optimum number of vehicles in the Top Ten Routes of Kathmandu Valley which was found from the 163 number of routes of our study on the basis of total travel demand measured in passenger-km per year. The transportation optimization model has been prepared on the Microsoft-Excel Spreadsheet & the optimization of distribution of vehicles is done by using Premium Solver. The results clearly show that the requirement of buses at some routes was less than the available buses plying on the route & the requirement of buses at some routes was more than the available buses plying on the route. The optimization is done on the basis of least cost methods fulfilling the travel demands of flow of passengers at different interval of time in a day at each route of our study. More number of required vehicles in the optimized scenario in the route means more transportation cost, more energy consumption & more environmental emissions than the present scenario & Lesser number of required vehicles in the optimized scenario in the route means lesser transportation cost, lesser energy consumption & lesser environmental emissions than the present scenario.