CTO Recommendation of Electronic Products Based on Particle Swarm Optimization Hybrid Ant Colony Optimization Algorithm

Youhua Yu, Xiao-Ian Xie, Yunlong Cui
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Abstract

In recent years, with the continuous innovation of science and technology, users' demand for electronic products gradually presents a diversified trend. However, there are a wide variety of electronic products in the market and the products are updated quickly, which brings great difficulties for users to choose. To solve the above problems, this paper proposes a particle swarm optimization hybrid ant colony optimization algorithm to solve the CTO (Configure To Order) recommendation model of high-end electronic products, so as to provide customers with unique personalized customization services for electronic products. The simulation results show that the algorithm has good performance in solving the CTO recommendation model of electronic products.
基于粒子群优化混合蚁群算法的电子产品CTO推荐
近年来,随着科技的不断创新,用户对电子产品的需求逐渐呈现出多元化的趋势。然而,市场上的电子产品种类繁多,产品更新快,给用户的选择带来了很大的困难。针对上述问题,本文提出了一种粒子群优化混合蚁群优化算法来解决高端电子产品的CTO (Configure To Order)推荐模型,从而为客户提供独特的电子产品个性化定制服务。仿真结果表明,该算法在求解电子产品CTO推荐模型方面具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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