Dynamic immune cooperative scheduling of agricultural machineries

Abstract Considering the low flexibility and efficiency of scheduling problem, an improved multi-objective immune algorithm with non-dominated neighbor-based selection Tabu search (NNITSA) is proposed. A novel (TSA)-based operator introduced in both local mutation stage, which improves climbing performance NNTSA. Special strategies can prevent from being caught optimal solution. In addition, considering time costs TSA, adapted strategy proposed to operate TSA according scale Pareto solutions. Random mutations may be applied other conditions. Then, a robust evaluation adopted choose appropriate solution obtained solutions set. NNITSA used solve problems static partitioning optimization dynamic cross-regional co-operative agricultural machinery. The simulation results show that outperforms two algorithms, NNIA NSGA-II. indicator C-metric also shows significant improvements optimizing search.