Optimal Worker Selection for Maximizing Quality-of-Service of Online Food Delivery System (original) (raw)

2019 International Conference on Sustainable Technologies for Industry 4.0 (STI)

Abstract

The selection of workers for carrying out tasks in mobile crowdsourcing systems that maximizes Quality of Service (QoS) is a challenging problem due to their diverse task completion properties and profit demands. The existing works in the literature are limited either by merely considering the minimization of task completion time only or exploitation of colocated locations of the worker and task. In this paper, we have developed an optimization framework to make a trade-off in between the profit of workers and task completion time. The proposed framework considers locations related to task's service point, task's delivery point and current location of the worker. The results of performance studies depict that the proposed system offers competitive task delivery time as well as workers' profit.

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