The application discloses a long-term multi-agent task
allocation method based on a multi-objective multi-level cultural
gene algorithm, which is used in a task continuous random arrival scene such as intelligent warehousing. In view of the problems that the existing static method cannot adapt to long-term tasks, the
online method is frequently cold started, the historical knowledge is poorly reused, the convergence is slow, and the task period and the agent load balancing are difficult to balance, a double-
objective model of minimizing cumulative task period and minimizing load deviation is established; a multi-objective multi-level cultural
gene algorithm is designed, multi-strategy initialization, hierarchical
population and genetic operation are adopted, adaptive multi-neighborhood and
confusion degree pop-up search local search are combined, and the
population and historical archives are updated by cooperating with the non-dominated solution sorting, congestion degree calculation and elite reservation strategy. Through the organic combination of the above strategies, the
algorithm can realize the collaborative optimization of task response and load balancing without interrupting the
system operation.