This paper presents a novel heuristic approach to solving the Pickup and Delivery Problem with Cooperative Robots (PDP-CR), a challenging optimization problem in automated warehouse logistics. The PDP-CR involves coordinating a fleet of robots to complete pickup and delivery tasks, some of which require multiple robots to cooperate. Our heuristic is designed to minimize the makespan by efficiently assigning robots to tasks while adhering to cooperation constraints. We compare the performance of our heuristic with an existing Mixed Integer Linear Programming (MILP) model through computational experiments on both small and large datasets. Results show that the proposed heuristic algorithm significantly reduces computation time while achieving good solutions, making it more suitable for large-scale applications.