Research on the Optimization of Supermarket Staff Scheduling Based on Intelligent Algorithm Combined with Binary Coding

This paper delves into the core problem of supermarket staff scheduling optimization, especially in terms of reducing human resource costs and increasing corporate profits. Genetic algorithm is adopted as the solution method, and the raw data are exhaustively preprocessed and converted into formats at the initial stage. During the application of the genetic algorithm, the Binary 0–1 gene coding method and targeted fitness function were designed. The staff scheduling was successfully optimized through genetic crossover, mutation, and elimination mechanisms. On this basis, employee qualification and efficiency are introduced as new optimization indexes, and the model and fitness function are adjusted accordingly to further enhance the effectiveness of the scheduling scheme.