首页> 外文会议>International symposium on neural networks >Application of Multi-objective Particle SwarmOptimization Algorithm in Integrated Marketing MethodSelection
【24h】

Application of Multi-objective Particle SwarmOptimization Algorithm in Integrated Marketing MethodSelection

机译:多目标粒子培养算法在集成营销方法中的应用

获取原文

摘要

Through multi-particle swarm optimization algorithm, this paper is aimed to solving the optimization problems of multi-production and multi-marketing strategy selection during the process of integrated marketing. In order to achieve benefit maximization, the fittest marketing method should be put in place into the marketing promotion of each product, which in fact is the problem of multi-objective optimization decision. During the optimization process, first of all, convert discrete variable into continuous variable through the equivalent probability matrix, then update particle swarm and normalize particle position, and finally complete the selection of particle individual extremum and the global extremum through decoding and fitness computing. The simulation results for the practical problem through this method show that the investment and rational-ized distribution of marketing methods can obtain better expected benefits. The conclusion is that multi-objective particle swarm optimization algorithm is an ef-fective method for solving the optimization allocation of products and marketing methods during the process of integrated marketing.
机译:通过多粒子群优化算法,本文旨在解决在整合营销过程中多产量和多营销策略选择的优化问题。为了实现利益最大化,应将最适合的营销方法放在每个产品的营销促进中,其实是多目标优化决定的问题。在优化过程中,首先,通过等效概率矩阵将离散变量转换为连续变量,然后更新粒子群和标准化粒子位置,最后通过解码和健身计算完成粒子个体极值和全球极值的选择。通过该方法的实际问题的仿真结果表明,投资和理性分布的营销方法可以获得更好的预期效益。结论是,多目标粒子群优化算法是一种EF - 综合营销过程中产品和营销方法优化分配的EF一般性方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号