Motivated by the necessity to reduce GHG emissions by commuting vehicles and improve users’ convenience, this thesis is dedicated to proposing an optimal network and management of Electric Vehicle (EV) charging stations on campus making the most of the zero tailpipe emissions of EVs. The problem has been decomposed with identified critical components to construct a basic Mixed Integer Programming (MIP) model maximizing the convenience benefits and minimizing the construction costs. Moreover, an expanded model has been proposed in accordance with another sub-objective of gaining greater environmental benefits. Two models are solved by CPLEX in Python with necessary inputs from several sources. Last but not least, the validity of the models has been verified by linearized relaxation, sensitivity analysis, and scenario analysis, which prove the enormous applicability and capability of two models.