Spare Parts Transportation Optimization Considering Supportability Based on Uncertainty Theory

Ensuring a consistent, continuous, and efficient spare parts supply is critical issue that must be addressed in the equipment support system. In order to effectively improve coverage level handle common asymmetry information present practical applications, transport vehicle routing scheduling model was further optimized. We integrated supportability requirements uncertainty theory into better describe actual uncertain demand of each site. selected three indicators as constraints, redefined them with variables, then completed chance-constrained on this basis. Once confidence specified, constraints can transformed deterministic finally, equivalent solved easily. addition, feasible solution found through genetic algorithm, numerical example provided validate model’s rationality. The proposed method successfully seeks balance between total cost supportability.