Discrete firefly algorithm with compound neighborhoods for asymmetric multi-depot vehicle routing problem in the maintenance of farm machinery

A baseline-reactive scheduling method for carrier-based aircraft maintenance tasks

Carrier-based aircraft maintenance tasks are conducted in time-critical, resource-constrained, and uncertain environments. Optimizing the scheduling allocation scheme of maintenance personnel and equipment, reasonably responding to uncertainty disturbances, and maintaining a high fleet availability are vital to the combat and training missions of carrier-based aircraft. The maintenance task scheduling problem for carrier-based aircraft is investigated in this study. First, a mathematical model for comprehensive carrier-based aircraft maintenance task scheduling that considers constraints such as maintenance personnel, equipment/shop, space, and parallel capacity is developed. Second, to generate the baseline scheduling scheme, an improved non-dominated sorting genetic algorithm II (I_NSGA-II) with local neighborhood search is proposed for the model optimization solution; I_NSGA-II uses the serial scheduling generation scheme mechanism to generate the time sequence scheduling scheme for maintenance personnel and equipment/workshop of different fleet sizes. Third, to cope with dynamic uncertainty disturbances, two reactive scheduling methods, i.e., complete rescheduling and partial rescheduling, are proposed to perform reactive scheduling corrections to the baseline schedule. Case simulation shows that the established mathematical model is reasonable and practical, and that the proposed I_NSGA-II is superior to the current mainstream algorithms. In addition, the decision maker can select between the two reactive scheduling methods flexibly based on the different forms and scales of disturbance.

Logistics Network Distribution Optimization Based on Vehicle Sharing

The development of the sharing economy has provided new ideas for a vehicle-sharing urban logistics network cooperative distribution strategy. In view of the lack of dispatching capacity or transportation capacity of logistics enterprises with multiple distribution centers, this paper proposes a vehicle-sharing urban logistics network cooperative distribution strategy. Based on the comprehensive consideration of a multi-distribution center, multi-model, rental vehicle, load, speed, fuel consumption, and other factors, the calculation method of vehicle energy consumption is introduced, the network collaborative distribution model with vehicle sharing is established, and an adaptive genetic algorithm combined with a scanning algorithm is designed. Finally, the validity and reliability of the mathematical model and algorithm are validated and analyzed by an example. The research results show that vehicle sharing can improve the efficiency of the distribution network and effectively reduce costs.