基于粒子群优化算法的中小企业竞争情报搜集系统模型

Competitive Intelligence Collection System Model for Small and Medium Enterprises Based on Particle Swarm Optimization Algorithm

摘要:

竞争情报搜集是企业竞争情报工作的重要环节，如何使情报人员对海量信息源进行价值排序，从而有效寻找高价值情报，是研究竞争情报搜集工作的关键课题。以粒子群优化算法为基本理论，结合我国中小企业目前对竞争情报的迫切需求和开展竞争情报工作的困难，利用跨学科分析法和仿真实验检验法，构建了一个适用于中小企业的竞争情报“粒子搜索模型”。该模型充分调用各粒子“经验”寻找全局最优解，用以为我国中小企业构建低成本、高收益、易组织管理的竞争情报搜集系统模型提供参考。

Abstract:

Collecting competitive intelligence is an important part for the competitive intelligence work of enterprise, and it is a key factor in the research of competitive intelligence collection process that intelligence personnel how to sort the value of massive information sources, and effectively search for high-value intelligence. This paper constructs a "particle search model" of competitive intelligence for small and medium enterprises(SMEs) by taking Particle Swarm Optimization Algorithm as the basic theory and using interdisciplinary analysis and simulation test method in view of the urgent demand for competitive intelligence and the difficulties in carrying out competitive intelligence work of SMEs in China. The model fully utilize the "experience" of each particle to find the global optimal solution, which can provide reference for SMEs in China to build a competitive intelligence collection system model with low cost, high income and easy organization and management.