Article

Intelligent Scheduling System for Service Industry Based on Ant Colony Algorithm

1 School of Mathematics and Computer, Guangdong Ocean University, 524088, Guangdong Zhanjiang China
2 College of Ocean Engineering and Energy, Guangdong Ocean University, 524088, Guangdong Zhanjiang China
3 College of Economics, Guangdong Ocean University, Zhanjiang 524088, China
# These authors contribute to this article equally.

https://doi.org/10.58531/esmmsi/1/3/7

Received: 24 July 2024 / Accepted: 24 August 2024 / Published: 26 August 2024

Staff scheduling management is crucial in the service industry, especially in restaurants, supermarkets, and retail stores. Currently, shift preparation work mainly relies on manual operations, leading to inefficiency in the field of shift management in the service industry. Traditional monolithic scheduling systems face issues such as difficulty in horizontal expansion, tight coupling between modules, and challenges in updating and maintenance as functions increase, making them unsuitable for dynamic scheduling needs. In order to solve these problems, this study adopts the ant colony algorithm combined with TPE-BP neural network, web technology, and microservice architecture to develop an intelligent scheduling system. This system is divided into multiple service modules according to function, which effectively reduces the system coupling degree. It is highly scalable and can schedule shifts automatically, flexibly and efficiently, which improves the efficiency of schedule generation, and provides the service industry with a more convenient and intelligent scheduling management tool.

Intelligent scheduling, Ant colony algorithm, Microservice architecture, Service industry

Chen X., Li Ch., Lu Y., Zhu J., Tang Y., Chen R., Ye M., Wu Yueyang 1, Cao Yo., Xi L., Cui J., Liu H., Ning D., Li Z. Intelligent Scheduling System for Service Industry Based on Ant Colony Algorithm. Eng. Solut. Mech. Mar. Struct. Infrastruct., 2024, 1(3), doi: 10.58531/esmmsi/1/3/7

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