Abstract
This paper presents a technique for integrating information about future customer requests to improve decision making for dynamic vehicle routing. We use a co-evolutionary approach to generate better waiting strategies such that the expected number of late-request customers who are served is maximized. An empirical evaluation of the proposed approach is performed within a previously reported hybrid genetic algorithm for the dynamic vehicle routing problem with time windows. Comparisons with other heuristic methods demonstrate the potential improvement that can be obtained through the application of the proposed approach.
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