Christof Defryn

TL;DR: An improved two-level heuristic to solve the clustered vehicle routing problem (CluVRP) by combining two variable neighborhood search algorithms, that explore the solution space at the cluster level and the individual customer level respectively.

TL;DR: A selective vehicle routing problem, in which customers belonging to different partners in a logistic coalition are served in a single logistic operation with multiple vehicles, and a central algorithm creates an operational plan including the decision on which customers to serve and in which trip.

TL;DR: The proposed solution framework is the first to include these objectives of the individual partner interests directly into the objective function of the optimisation model.

TL;DR: The results confirm that, even in a situation in which each partner has multiple, possibly conflicting objectives, joining a horizontal logistics coalition can be beneficial for all partners, and the coalition efficiency approach is able to find good quality solutions with less calculation time, but lacks robustness.

TL;DR: In this article, the authors focus on the challenge of dividing the total coalition gain among all partners in a logistic co-operation and examine the impact of defining gain defining gain sharing on a short term (daily) or a long term (monthly) basis.