Stochastic Vehicle Routing Problem with Uncertain Demand and Travel Time and Simultaneous Pickups and Deliveries

Aiming at the stochastic vehicle routing problems with uncertain demand and travel time and with simultaneous pickups and deliveries, a stochastic programming model is formulated and an improved genetic algorithm is proposed for routes optimization. Self-adaptive mechanism is introduced for amending the fitness value to overcome the premature convergence effectively and to improve the efficiency of the algorithm. The performance of the algorithm is discussed under a variety of problem settings and parameters value by the numerical experiments and sensitivity analysis. Results demonstrate that not only the proposed algorithm obtains even better results, but also it has a good robustness.