Platform for optimizing and scheduling task

Abstract

The invention discloses a task optimal scheduling platform which comprises a task information interface module used for receiving task information generated by a task generation system; a data storage module used for storing the information of task execution staff; a task scheduling module used for storing optimal scheduling rules, carrying out matching treatment to the task information received by the task information interface module and the information of task execution staff stored in the data storage module according to the stored optimal scheduling rules, selecting the information of the task execution staff matched with the task information and transmitting the information; and an interaction module used for receiving the information of the task execution staff selected by the task scheduling module and transmitting task information to a terminal according to the received information of the task execution staff. Based on the optimal scheduling rules, the task optimal scheduling platform automatically schedules task execution staff for each task generated by the task generation system, thereby realizing the task unity and automatic human resource scheduling in large activity.

Description

technical field [0001] The invention relates to computer technology, in particular to a task optimization scheduling platform, which belongs to the field of network communication. Background technique [0002] In large-scale activities, a large number of on-site task performers are required to complete various tasks. Generally, large-scale activities have the following characteristics: task performers are distributed in different places; the location and content of various tasks are not fixed; the completion of a task requires many aspects such as personnel skills and completion time; tasks may change at any time and there are new ones. task is generated. Therefore, in large-scale activities, it is the key to successfully hold large-scale activities to conduct unified human resource scheduling in order to complete various tasks quickly and efficiently. [0003] In the prior art, human resources are usually divided according to different places, and the task performers in a...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, human resources are usually divided according to different places, and the task performers in a certain place are only responsible for the tasks in that place, which easily leads to a problem: when there are many tasks in a certain place and the execution When the number of task executors is insufficient, task executors in other places who do not perform tasks cannot be transferred to places with more tasks to perform tasks; correspondingly, task executors in places with fewer tasks will be idle. Happening

In addition, in the process of scheduling human resources in various places, it is usually to use manual methods to judge tasks and select appropriate task executors to perform tasks. This manual method is not only difficult to guarantee when there are many tasks. Reasonably schedule task executors for each task, and the efficiency is low

[0004] To sum up, there is no solution in the prior art that can well solve the problem of unifying tasks for large-scale activities and automatically scheduling human resources

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