European firms have been using a combination of trucks and trailers in the delivery/collection of food products for years. Most of the studies on the truck and trailer routing problems (TTRP) assume the vehicle traveling time is a definite value. However, traffic congestion, road maintenance and traffic restriction, vehicle damage or other accident factors will lead to the uncertainty of driving time in practice. This paper studies a version of stochastic TTRP, in which travel and service times are stochastic, and a time window constraint is associated with each customer. This problem is formulated as a chance constrained programming model with recourse in terms of different optimization criteria. To efficiently solve this model, a heuristic based on Tabu searching, which accounts for the stochastic nature of this problem, is then proposed. Finally, a testing instances is established to investigate the algorithmic performance, the computational results is then reported and discussed.
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