Optimization method of tobacco logistics warehouse space allocation based on improved genetic algorithm with population strategy and parent selection strategy

In this paper, a multi-objective optimization model with shelf stability, goods access efficiency, goods relevance, first-in-first- out, and equipment load balancing as optimization objectives is established for the optimization problem of storage space in a multi-storey shuttle truck three-dimensional warehouse. According to this model, an improved multi-objective genetic algorithm (NSGA-II) is proposed to address the shortcomings of the traditional multi-objective genetic algorithm, introduce the initial population generated by the optimization of the set of good points, change the characteristics of the initial population generated randomly, and solve the problem of uneven distribution of the population in space. (1) By adopting the parent generation selection based on linear ranking, the main idea is that the individuals of the population are ranked according to the adaptation value from small to large, and the added index term is gradually adjusted with the number of generations. In NSGA-II, the rank is first sorted in descending order, and then the crowding distance is sorted in ascending order. This method ensures the search ability in the early stage of the algorithm to expand the search space to avoid falling into the local optimum, and increases the pressure on the selection of the parent generation in the later stage of the algorithm to ensure that the algorithm's convergence speed can be better approximated to the real value. (2) Change the model evaluation method, in order to assess the uniformity and breadth of the distribution of the solution set, this paper adopts the spatial evaluation method to assess the distribution of the algorithm. Experiments under different order sizes show that the improved NSGA-II improves the performance of the algorithm by more than 45% compared with the traditional NSGA-II algorithm, and the overall performance is more significant and more suitable for dealing with the cargo space optimization problem, and it is an effective method for solving the optimization problem of the storage space in the multi-storey shuttle truck three-dimensional warehouse.