An adaptive immune‐following algorithm for intelligent optimal schedule of multiregional agricultural machinery

Abstract

Aiming at low efficiency of agricultural machinery scheduling, this paper proposes an adaptive immune-following algorithm (AIFA) based on immune algorithm and artificial fish swarm algorithm. The adaptive crossover operator is used to accelerate convergence, and adaptive mutation operator ensures good diversity of population. After the adaptive evolution operations are performed, the following operator based on the following behavior of artificial fish swarm algorithm is embedded into the algorithm, which improves the convergence precision and obtains the promising optimization results. Experiments on scheduling considering the breakdown of agricultural machinery are performed based on multiple regions and multiple agricultural machineries. Compared with the immune algorithm and genetic algorithm, the simulation results demonstrate that AIFA can converge faster and achieve a better optimal solution.

Task Allocation of Multi-Machine Collaborative Operation for Agricultural Machinery Based on the Improved Fireworks Algorithm

“…Zhai et al performed path planning for master-slave agricultural machinery, where the paths for slave operations were formulated based on the relative distances of the master and slave and the turning states to avoid collisions [10]. Jiang et al proposed an adaptive immune following algorithm based on the immune algorithm and artificial fish swarm algorithm to assign fields with a different amount of work to the agricultural machinery group [11]. Wang et al divided the path planning methods between the fields into several categories according to the positional relationship between the fields and assigned the fields to the agricultural machinery group accordingly [12,13].…”

“…The distance between the garage and the n fields is represented by a square matrix D d of order (n + 1) with a diagonal of zero, as shown in Equation (11), where the first row (column) represents the garage, and rows (columns) from the second row (column) to the last row (column) represent n fields.…”

Selective disassembly sequence optimization based on the improved immune algorithm

“…Zhang et al (2014) renamed parts according to their positions, and the hybrid PSO-IA is proposed for the specific assembly sequence planning. Jiang et al (2022) proposed the adaptive immune‐following algorithm to solve the agricultural machinery scheduling problem and achieved promising results.…”

A method of automatic mechanical control based on single chip microcomputer

“…In many places, traditional ginger lifting appliances, ploughs or lifting are still used, which is very inconvenient to harvest ginger. [1][2][3][4][5][6][7][8][9] At present, rural modernization has been attached great importance. However, due to the sharp decrease of agricultural population and the low level of intelligent agricultural production machinery in the agricultural production field of China, farming has become a problem, and a lot of farmland has been abandoned.…”