Optimal Design of Crowdsourcing Project Pricing

Aiming at the problem of the pricing and completion of crowdsourcing project,. we set up a project task pricing design model and solve this model by using genetic algorithm and logistic regression. Meanwhile, we use the differential equation to improve this model. The project task pricing design model is a multi-objective nonlinear programming model. We introduce the concept of company profit to limit the price and regard the profit as our target function. In addition, we consider the members' credit value, the distance between the members to the mission point, the number of members within the mission area and the possibility of members performing tasks to limit target function. In consideration of the possibility of the member performing the task, we used the logistic method to fit it. When considering the integrated reputation of members, we use the entropy weight method to determine the coefficients of each index. Finally, we get the target function values in different cases by using Genetic Algorithm. Meanwhile, we use the differential equation method to set up the price floating model to optimize our existing model. Through the model we established, we can ensure that the tasks issued by the company can be carried out with a higher completion rate in practice, and obtain better profit.