Objective By optimizing the sorting trajectory of Delta robots, while ensuring sorting accuracy, this paper aims to reduce comprehensive energy consumption, shorten operating time, and minimize operational impact.Methods Based on the analysis of automated food production lines, a trajectory optimization method for food sorting-oriented Delta robots was proposed, which combined 5-order non-uniform rational B-spline curves, multi-objective optimization, and multi-objective evolutionary algorithms based on decomposition. By taking comprehensive energy consumption, operating time, and operational impact as optimization objectives, an improved multi-objective evolutionary algorithm based on decomposition was used to solve and verify 5-order non-uniform rational B-spline curves.Results This method has improved the efficiency of the food production line (reducing operating time by 5.00%), extended the service life of equipment (reducing operational impact by 17.32%), and reduced food loss.Conclusion The combination of 5-order non-uniform rational B-spline curves and multi-objective optimization can effectively balance the high-speed and smooth operation of Delta robots.