As the reverse logistics and the closed loop supply chain networks have been adopted by enterprises, the delivery and pickup problems with time windows have much attention and have been studied extensively. After investigating their uncertainty properties and complexities in finding solutions, this study, based on the Fuzzy Credibility Theory, proposes a Chance Constrained Programming (CCP) model to describe a Fuzzy Flexible Delivery and Pickup Problem with Time Windows (FFDPPTW). In the meantime, a Coevolutionary Algorithm is implemented to obtain near optimal solutions in an acceptable computational time. Some test problems are generated by revising the well-known Solomon’s benchmarks which are originally used for the vehicle routing problem with time windows. The results show the coevolutionary algorithm is not only accurate but more efficient. Further comparison between different confidence levels shows that the higher the confidence level is required, the larger the cost is paid; this facilitates the decision support based on the decision maker’s preference.

routing, delivery and pickup, time window, uncertain demand, fuzzy credibility, coevolutionary algorithm.