Supply Chain Management and Genetic Algorithm: introducing a new hybrid genetic crossover operator

The increase in the Brazilian consumer market in recent years has allowed the opening of new stores, increasing price competition and diversifying the product offering. However, finding the best combination of price, quality and services, considering the cost of transport between stores is a very hard task. The complexity of the problem increases when more products and stores were involved. This is a classical problem in supply chain network design. The effective management of the supply chain is recognised as one of the most important factors in modern business management. In this paper, we propose a new hybrid operator for genetic algorithm used to optimize the purchase of products in stores geographically separated in order to obtain solutions that combine the purchase of products with the lowest possible total cost, considering the route between each store.