Evaluation of Rational Layout of Retail Outlets for Proprietary Goods Based on Local Multi-objective Optimization

The rationalization of the market layout of retail outlets for franchised goods is more special for ordinary goods. From the perspective of data analysis and machine learning, this paper proposes a new evaluation model for the rational layout of retail outlets based on multi-objective optimization. According to the distribution density of retail stores, the complete area is divided into local sub-areas by two-step clustering, and the optimal solution of retail store layout is obtained by using multi-objective genetic algorithm for the original layout of retail stores in different sub-areas. The optimal solution of each sub-areas is integrated to get the final optimal solution of the retail store layout. Besides, the optimal solution in retail locations rationalization layout application design method is presented. Based on a tobacco franchise monopoly, a data set of cigarette retail locations in city A was utilized to test the method proposed in this paper. The experimental results indicate that our method can effectively assess the distribution of retail outlets in the region and offer a better evaluation. Furthermore, building on the optimal solution, a rational design for the layout of tobacco monopoly retail outlets in the city is presented.