Energy consumption of large commercial buildings has become higher than before, and a major part of the energy is on their lighting systems. This thesis aims at reducing the energy consumption of a building's lighting system. Our solution is to minimize the total number of necessary light fixtures in a commercial building, and thus we formulate the Constrained Light Deployment Problem (CLDP). The CLDP problem is tightly related to the Art Gallery Problem (AGP), a classical problem in computational geometry that finds the minimum number of guards to monitor a polygon area. Unlike the traditional AGP, however, our problem poses a new challenge that the illuminance of any spot in the building must be higher than a required threshold. To address the new challenge, we first propose an algorithm based on polygon partition and iteratively remove redundant light fixtures to obtain a tighter upper bound on the necessary number of light fixtures. We further improve the algorithm with clustering and binary search to reduce the number of light fixtures. Our algorithm can return the locations of resulted light fixtures, which are not necessarily the vertices of the orthogonal polygon. Simulation results demonstrate that our algorithm is fast and effective. / Graduate