Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching
Transportation Science
Runtime reduction techniques for the probabilistic traveling salesman problem with deadlines
Computers and Operations Research
A survey on metaheuristics for stochastic combinatorial optimization
Natural Computing: an international journal
SLS'07 Proceedings of the 2007 international conference on Engineering stochastic local search algorithms: designing, implementing and analyzing effective heuristics
The Vehicle Routing Problem with Stochastic Demand and Duration Constraints
Transportation Science
An ant based simulation optimization for vehicle routing problem with stochastic demands
Winter Simulation Conference
A Branch-and-Price Algorithm for the Capacitated Arc Routing Problem with Stochastic Demands
Operations Research Letters
Particle Swarm Optimization for the Vehicle Routing Problem with Stochastic Demands
Applied Soft Computing
Proceedings of the 15th annual conference on Genetic and evolutionary computation
| Hi-index | 0.00 |
In this paper, a stochastic vehicle routing problem is considered. In particular, customer demand is assumed to be uncertain, and actual demand is revealed only upon the visit to the customer. Instead of adopting the simple recourse action of returning to the depot whenever the vehicle runs out of stock, the points along the route at which restocking is to occur are designed into the route. The restocking points may be before a stockout actually occurs. Two heuristic algorithms are developed to construct both single and multiple routes that minimize total travel cost. The computational results show that the heuristic procedures produce quality solutions and are efficient.