The vehicle scheduling problem with intermittent customer demands
Computers and Operations Research
Computers and Operations Research - Neural networks in business
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Parallel Tabu Search for Real-Time Vehicle Routing and Dispatching
Transportation Science
Diversion Issues in Real-Time Vehicle Dispatching
Transportation Science
A Rollout Policy for the Vehicle Routing Problem with Stochastic Demands
Operations Research
A Compressed-Annealing Heuristic for the Traveling Salesman Problem with Time Windows
INFORMS Journal on Computing
The A Priori Dynamic Traveling Salesman Problem with Time Windows
Transportation Science
Waiting Strategies for Dynamic Vehicle Routing
Transportation Science
Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching
Transportation Science
Waiting Strategies for Anticipating Service Requests from Known Customer Locations
Transportation Science
ASAP: The After-Salesman Problem
Manufacturing & Service Operations Management
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Advances in information technology and telecommunications, together with ever-growing amounts of data, offer opportunities for transportation companies to improve the quality of the service that they provide to their customers. This paper compares two methods motivated by the opportunity that the availability of data and technology gives to improve on current practice. In particular, the two solution approaches are explored in the context of a dynamic and stochastic routing problem in which a single, uncapacitated vehicle serves a set of known customers locations. One approach, sample-scenario planning, offers the potential for higher-quality solutions, but at the expense of greater computational effort. On the other hand, anticipatory insertion offers reduced computation and increased managerial ease, but with the potential for reduced solution quality due to restrictions on solution structure. Our results show that anticipatory insertion can often match the quality of sample-scenario planning, particularly when the degree of dynamism is low.