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《Electronic Test》 2018-11
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Research on crowdsourced task pricing model based on objective optimization algorithm

Zhang Huanqing;Xu Qinghao;Pan Yifan;College of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications;  
In order to reasonably set the price of the task in the network crowdsourcing platform, this paper establishes a single-objective optimization model of task pricing by balancing the total task price and task completion rate as objective functions. The task completion rate was found to increase by 40.2% over the original scheme. Then, considering the user scramble that may result from the concentration of task location, a multi-objective optimization model of crowdsourcing task is established with the objective function of minimizing the reduction of individual task pricing and the minimum difference between the profit of members, the task completion rate and the maximum pricing ratio. It was found that when the task overhead only increased by 5.54%, the task completion rate increased by 10.8%. Therefore, the model of crowdsourced task pricing model established in this paper has certain reference value and guiding significance for the research of crowdsourcing task price.
【CateGory Index】: F274;TP18
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