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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.