Optimal Schedule for Agricultural Machinery Using an Improved Immune-Tabu Search Algorithm

Considering the low efficiency and lack of intelligent dispatching decision of the agricultural machinery scheduling problem, an improved Immune-Tabu Search Algorithm (ITSA) based on the immune optimization algorithm is proposed. A new operator, named TSA, is designed through improvement on the generation of neighborhood solution based on the tabu search algorithm. At the beginning of the iterations, the algorithm makes use of the search results of TSA as the mutated antibodies, so as to improve the climbing performance of the algorithm and accelerate the convergence speed in the meantime. Then, random mutation and tabu search for parallel strategies are implemented to ensure the optimization of the result as well as shorten the optimization time. Compared with the immune optimization algorithm and tabu search algorithm, the simulation results show that ITSA can not only obtain a better search success rate, but also stabilize the results of the algorithm.