众包商业模式下的任务定价方案研究

Research on Mission Pricing Scheme under Crowdsourcing Business Model

摘要: 本文对移动互联网的自助式劳务众包平台进行研究，建立了基于多元线性回归模型下的任务定价模型。与原方案进行对比，改进后模型的任务完成率达到67.305%，相对于原方案的62.395%有了明显提高，并且任务相对支出整体上降低，优化效果较好。进一步，根据对任务“打包发布”方式的分析，进行了基于支持向量机样本分类原理下的仿真模拟，在问题二的基础上添加打包规则、更改仿真规则，并且引入贪心算法的思想建立打包机制，改进之前建立的定价方案。经求解，得出改进后的模型中，任务完成率提高到72.302%，整体任务完成情况较好。本文所涉及数据来自于2017年全国大学生数学建模竞赛B题。

Abstract: This paper studies the self-service crowdsourcing platform of mobile Internet, and establishes the task pricing model based on multivariate linear regression model. Compared with the original plan, the completion rate of the improved model reached 67.305%, which was significantly higher than 62.395% of the original plan. And the overall relative reduction of mission expenditure, op-timization effect is better. According to the analysis of the task “package release”, we carried out the simulation based on the principle of support vector machine (SVM). On the basis of the second problem, the rules of packing are added, and the rules of simulation are changed, thus introducing the idea of greedy algorithm to establish the packing mechanism to improve the pricing scheme established before. After solving, in the improved model, the task completion rate increased to 72.302%, and the overall task is completed better. This article involves the data from the National Undergraduate Mathematical Contest 2017 Modeling B questions.