In the present contribution, the application of a dynamic pick-up and delivery model for hospital internal logistics is investigated. Two scheduling policies are developed: the first applies a cheapest insertion heuristic targeting optimization of the problem's objective function, while the second employs local search to improve the current schedule. A computational study is presented in which the two policies are applied on a range of generated problem instances that have been made available to the research community. The benefit of the two policies is demonstrated by comparing them with a common and intuitive earliest first, by due date policy. Secondly, the benefit of allowing to combine transports is also investigated, and it is shown that this may lead to further increased performance.
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