Improved discrete imperialist competition algorithm for order scheduling of automated warehouses

Abstract

An improved discrete imperial competition algorithm (DICA) is proposed for the multi-objective order scheduling problems of automated warehouses. The aim is to minimize the completion time of all orders and the total tardiness of outbound orders. The priority value, influenced by the importance and relative cut-off time of the orders, as well as the number of tasks, is designed to sort the orders. Similar to the genetic algorithm (GA), the assimilation process of the improved DICA is constructed by crossover and mutation. Meanwhile, Hamming distance is introduced to verify the quality of assimilation. Taking a practical case as an example, the improved DICA is used to solve two scheduling strategies: outbound order priority scheduling and compound order scheduling. The main results show that the compound order scheduling can be performed effectively, especially when the number of orders is large, the completion time and total tardiness can be greatly reduced. In addition, compared with GA, the solution quality of the improved DICA is better, but its convergence speed is slower.