Supply chain management consists of optimising production process from raw material sourcing to final product, logistics and delivery to the final customer. In this context, we propose for the first time the hybridization of two metaheuristic algorithms, the cat swarm optimization and the genetic algorithm, for a simultaneous resolution of the open shop scheduling problem with the vehicle routing problem. The objective function is to minimize the end date of workshop process called makespan and the total traveled distance by the vehicles. The computational experiments were performed based on well-known benchmark data instances. The generated results were compared with the best approaches of the literature, in terms of generated solutions and processing time, in order to show the effectiveness of the proposed approach.