Carpooling is an effective transport model that can significantly reduce transportation costs. The problem to match passengers with drivers is a difficult problem due to complex constraints to be satisfied in the solution processes. The goals of this paper are to propose a model and a solution methodology that is seamlessly integrated with existing geographic information system to determine drivers/passengers for ride sharing. In this paper, we formulate a car pooling problem and propose a solution algorithm for it based on a meta-heuristic approach. Differential evolution (DE) is a competitive evolutionary algorithm widely utilized in the science and engineering fields. The simple and straightforward evolving mechanisms of DE endow it with the powerful capability to solve optimization problems. To achieve the goal, we first formulate the carpooling optimization problem as an integer programming problem. We then develop variants of DE algorithm for it. We also conduct experiments to illustrate and compare effectiveness of the proposed DE algorithms.