Airport ground-handling companies want to improve their operations all around the world want by automating current processes, and finding extra optimizations otherwise unreachable for human dispatchers. We aim to address the catering problem in the crossover between vehicle routing problems and scheduling problem, also known as the simul- taneous supply & delivery problem. The MTCVRSPTW-MB (Multi- Trip Capacitated Vehicle Routing and Scheduling Problem with Time Windows and Meal Breaks) is extended to a heterogeneous fleet of trucks and drivers, with qualifications and different load patterns. We introduce a greedy heuristic to solve a relaxed version of the problem, as a baseline. Then, we implement a cooperative rVNS-based meta- heuristic. We compare our algorithms on multiple real-life instances at San Francisco International Airport. Our computational study shows the effectiveness of each approach and brings out the strength of our metaheuristic. Our algorithms will help ground handlers specialized in catering operations, to speed up the decision-making process of assign- ing hundreds of tasks every day. In particular, we show the multiple extra benefits of the metaheuristic approach, including minimizing fuel consumption and the ability to re-assign tasks dynamically.