Multi-objective Pick-up Point Location Optimization Based on a Modified Genetic Algorithm

To solve the logistics terminal distribution problem, we construct the multi-objective location allocation model of pick-up point. The model considers the characteristics of express logistics system, enterprise demand and customer demand for delivery distance, and two objectives of minimizing location cost and maximizing customer distance satisfaction are included. We set the segmentation distance function according to the distance of the user from the pick-up point, and calculate the satisfaction function. To solve the model, we modify the non-dominated sorting genetic algorithm with elite strategy algorithm (NSGA-II). Consider the needs of the enterprise or user, we modify the crossover operator, and use the tournament method to evaluate the offspring population generated by genetic operations to reduce the loss of elite individuals. We also verify the effectiveness of the model and the modified algorithm through experiments. Experimental results show that the modified algorithm can obtain a better Pareto optimal solution set for the multi-objective location-allocation problem.