Design and Application of Intelligent Scheduling System Based on Business and Labor Forecasting

Wang Zhongyi | Gong Rui | Jiang Wen | Yang Yang ^[4] | Gou Yangsiyu

Abstract: This paper presents an intelligent scheduling system based on business and labor prediction, aimed at addressing the issue of understaffing during peak periods and resource idleness in trough periods in the catering industry. The algorithm design employs Long Short-Term Memory network (LSTM) for passenger flow prediction and genetic algorithm for optimizing staff scheduling to achieve labor demand assessment, work efficiency maximization, and labor cost simplification. The back-end is developed using Java language with SpringBoot framework, while Vue.js and Element-UI are used for front-end development. Data storage is implemented using MySQL database with Redis as cache. The system primarily targets the catering industry.

Keywords: Springboot, Vue, Scheduling, LSTM, Genetic Algorithm, Catering

Edition: Volume 13 Issue 3, March 2024,

Pages: 1174 - 1176