Multi-product Pricing Method Based on Improved Ant Colony Algorithm

摘要

Integrating with the due-date and quality demand of customers, a dynamic pricing model with stochastic demand and capacity constraint which aimed to maximize total profit and average quality was established for the multi-product pricing problem with random parameter. A weight space ant colony optimization algorithm (WSACO) was proposed, which allowed ant's search direction to adjust dynamically according to the current Pareto solutions, thus improving the global searching capability efficiently. Compared to the Bi-criterion Ant (BIANT) algorithm, it obtains higher solving accuracy, the results also show that the WSACO algorithm presents better performance in improving profit and product quality and provides method support for multi-product pricing decisions of enterprises.