This paper describes an innovative approach to optimize the delivery process using genetic algorithms. The focus of the study is on the two-stage process: first, the process of allocating the salesmen to the customer in such a way that the total time required for visiting all points gets minimized; the second process is the optimization process of allocating suppliers to the customers that would minimize the shortage or overage of the product. The algorithms use balance load vertical crossover and equivalent mutation. Algorithms tested on real data include customers’ locations; they include the time needed for a journey along with any number of other real-life use cases. This study explores logistics optimization possibilities, focusing on the potential of genetic algorithms to address modern supply chain optimization challenges.