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In recent years new insights and algorithms have been obtained for the classical, deterministic vehicle routing problem as well as for natural stochastic and dynamic variations of it. These new developments are based on theoretical analysis, combine probabilistic and combinatorial modeling, and lead to new algorithms that produce near-optimal solutions, and a deeper understanding of uncertainty issues in vehicle routing. In this paper, we survey these new developments with an emphasis on the insights gained and on the algorithms proposed.
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