Vehicle Scheduling Model for Fresh Agriculture Products Pickup with Uncertain Demands

Abstract

A chance-constrained vehicle scheduling model for fresh agriculture products pickup with uncertain demands is proposed in this paper. The uncertain measure that vehicle loading will not exceed capacity constraint is presented in the model because of the uncertainty of demands. Based on uncertainty theory, when the demands are some special uncertain variables with uncertainty distribution such as linear, zigzag and normal uncertain distribution etc., the model can be transformed to a deterministic form and solved by genetic algorithm. When the demands are general uncertain variables, a hybrid genetic algorithm with uncertain simulation is presented to obtain the optimal solution. At last, to illustrate the effective of the model and algorithm, and to analyze the impact of parameters on model solution, an experiment is provided.