Multi-objective optimization for scheduling multi-load automated guided vehicles with consideration of energy consumption

The widespread implementation of modern logistics has led to the extensive use of multi-load automatic guided vehicles (m-AGVs) in automated sorting centers. This paper tackles one of the most challenging problems in this context, i.e., the scheduling of m-AGVs for express package handling. We comprehensively consider the loading and unloading delay of packages and energy consumption of m-AGVs, formulating the problem as a multi-objective mixed integer program (MO-MIP). To solve the proposed optimal scheduling problem, we apply the Non-dominated Sorting Genetic Algorithm (NSGA-II). A series of simulation experiments on three sorting centers have been further conducted to demonstrate the effectiveness and efficiency of the proposed model and solution algorithm.