Abstract

According to the analysis of indetermination between completion rate and remuneration of photo tasks in crowd sourcing mode, this study proposes relation curves that completion rate varies with remuneration and ranking of remuneration in the unit area inferred by cubic-Hermite interpolation method based on task data in Guangzhou and Foshan. Then this study uses Simulated Annealing Algorithm to find the optimal remuneration scheme which means that the task completion rate significantly increases with the small increase in the remuneration. This study also compares the scheme obtained by Simulated Annealing Algorithm with the initial scheme and finds that the task completion rate increased by 13.65%, while the total task remuneration increased by 1.17%. The results show that this optimization scheme is beneficial and reasonable.

Keywords:

Crowdsourcing, cubic-hermite interpolation method, optimization, photo tasks, simulated annealing algorithm,

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Competing interests

The authors have no competing interests.

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The authors have no competing interests.