Optimization of vegetable commodity pricing based on particle swarm algorithm and sparrow search algorithm
DOI:
https://doi.org/10.54097/fwvsct33Keywords:
Vegetable Products, Pricing Replenishment Strategy, Particle Swarm Optimization Algorithm, Sparrow Search Algorithm, Planning Model.Abstract
With the improvement of people's living standards, small and medium-sized supermarkets have become important places for people to buy groceries in their daily lives due to their complete range of product categories, guaranteed quality, and accessibility to residential areas. However, due to the characteristics of vegetables being greatly affected by weather, difficult to store, and having a large regional preference, most small and medium-sized supermarkets need to purchase them daily and maximize profits within limited sales space. Therefore, building a model to meet the needs of short-term pricing and replenishment strategies for small and medium-sized businesses has important practical significance. This article establishes a multi-objective programming model based on historical sales data of supermarkets, and uses sparrow search algorithm and particle swarm optimization algorithm to improve the accuracy of results, making scientific and reasonable strategic planning for small and medium-sized supermarkets to purchase goods.
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