Dynamic Scheduling Optimization of Agricultural Machinery Maintenance Service and Platform Development and Application

In the process of cross region operation of harvesters in busy agricultural seasons in China, due to the lack of effective maintenance service scheduling strategies in agricultural machinery enterprises, there are problems such as unreasonable configuration of maintenance service vehicles, waste of service costs and low flexibility. In the paper, the mathematical model of scheduling route of agricultural machinery maintenance service vehicle was constructed, and the location of agricultural machinery failure point and the maintenance time window were considered. With the objective of minimizing the operation and maintenance cost, the number of service vehicles and vehicle routing within the service request were optimized. The improved particle swarm optimization algorithm was adopted, and the crossover operation and heuristic factors in the genetic algorithm were introduced to avoid the local optimization phenomenon of PSO algorithm during the iterative process. The diversity of the population was expanded and the accuracy of the algorithm was improved. Through simulating and solving the scheduling mathematical model and the dynamic scheduling mathematical model after 2h. The status of each service vehicle and the newly added maintenance information were considered in the design of dynamic scheduling algorithm, so as to solve the re-planning of service routes of service vehicles at time t. In the analysis of simulation results, the service vehicle scheduling algorithm showed a good optimization effect. Finally, a service vehicle maintenance service scheduling system platform was designed and developed to realize the application of the algorithm in maintenance service scheduling management, providing an optimized solution for the after-sales maintenance service scheduling problem of enterprises.