基于单目标优化的众包任务定价模型
Pricing Model of Crowdsourced Tasks Based on Single-ObjectiveOptimizing Model
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摘要: 该文针对拍照赚钱APP的众包任务定价问题,考虑区域定价的差异下,基于曲线拟合工具和K-Means聚类分析算法,通过SPSS软件综合分析得出众包任务价格与区域生活水平、时间成本、人均任务数和任务难度系数等因素之间的定价规律,建立了以任务价格为决策变量、以众包平台利润限度为约束条件、以区域任务完成率最大化为目标的单目标优化模型,并建立了新的任务定价方案。在考虑将任务打包发布情况下,对定价模型进行修正,通过蒙特卡洛模拟法,给出模拟的实施效果。Abstract: This paper aims at the crowdsourced tasks pricing problem for app ofMaking Money by Photographing.Considering the difference of regional pricing,the algorithm is based on curve fitting tool and K-Means clustering analysis algorithm.The statistic package for social science(SPSS)software is used to analyze the pricing rules of the package task and the regional living standard,the time cost,the per capita task number and the task difficulty coefficient.A new single objective optimization model is set up,which takes the task price as the decision variable,the profit limit of the public package platform as the constrain condition and the goal of maximizing the completion rate of the regional task.Considering that the task is packaged and released,the pricing model is modified,and the implementation effect of simulation is given by Monte Carlo simulation.