This paper addresses urban traffic signal control in a scheduling framework, where the dynamics of an urban traffic network controlled by traffic lights is described by a novel model, which inserts mixed logical constraints into a cell transmission flow dynamic model, capable of capturing the nonlinear relationship between each outgoing link flow rate and the corresponding upstream and downstream link capacities and the past traffic light signals. With a control goal of minimizing the total network-wise delay time, we translate the traffic signal control problem into a centralized mixed integer linear programming problem solvable by several existing tools, e.g., CPLEX. To overcome the potentially high complexity involved in the centralized approach, we propose a distributed scheduling strategy based on Lagrangian relaxation and subgradient method. Simulation results are provided to demonstrate the effectiveness of the proposed traffic light scheduling approach.