A hybrid algorithm of particle swarm optimization and genetic algorithm with application in automatic replenishment model

This paper proposes a hybrid algorithm of particle swarm optimization and genetic algorithm named PSO-GA, which combines the advantages of genetic algorithm’s population diversity and stochastic global search and particle swarm optimization algorithm’s memory and fast convergence. The hybrid algorithm is then used to build an automatic replenishment model to help replenishment decisions by combining the idea of solving 0-1 knapsack problem. Using the sales data of a supermarket, we verify the feasibility and accuracy of the model, and the proposed algorithm can well solve practical problems in life.