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- W2116283846 abstract "We propose a dynamic traveling salesman problem (TSP) with stochastic arc costs motivated by applications, such as dynamic vehicle routing, in which the cost of a decision is known only probabilistically beforehand but is revealed dynamically before the decision is executed. We formulate this as a dynamic program (DP) and compare it to static counterparts to demonstrate the advantage of the dynamic paradigm over an a priori approach. We then apply approximate linear programming (ALP) to overcome the DP's curse of dimensionality, obtain a semi-infinite linear programming lower bound, and discuss its tractability. We also analyze a rollout version of the price-directed policy implied by our ALP and derive worst-case guarantees for its performance. Our computational study demonstrates the quality of a heuristically modified rollout policy using a computationally effective a posteriori bound." @default.
- W2116283846 created "2016-06-24" @default.
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- W2116283846 date "2014-10-01" @default.
- W2116283846 modified "2023-10-08" @default.
- W2116283846 title "A Dynamic Traveling Salesman Problem with Stochastic Arc Costs" @default.
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- W2116283846 doi "https://doi.org/10.1287/opre.2014.1301" @default.
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