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Monge Properties, Optimal Greedy Policies, and Policy Improvement for the Dynamic Stochastic Transportation Problem

机译:Monge属性,最佳贪婪政策,动态随机运输问题的政策改进

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We consider a dynamic, stochastic extension to the transportation problem. For the deterministic problem, there are known necessary and sufficient conditions under which a greedy algorithm achieves the optimal solution. We define a distribution-free type of optimality and provide analogous necessary and sufficient conditions under which a greedy policy achieves this type of optimality in the dynamic, stochastic setting. These results are used to prove that a greedy algorithm is optimal when planning a type of air-traffic management initiative. We also provide weaker conditions under which it is possible to strengthen an existing policy. These results can be applied to the problem of matching passengers with drivers in an on-demand taxi service. They specify conditions under which a passenger and driver should not be left unassigned.
机译:我们认为运输问题的动态随机延伸。 对于确定性问题,有知名的和充分条件,贪婪算法实现了最佳解决方案。 我们定义无分发类型的最优性,并提供类似的必要和充分条件,在这种情况下,贪婪的政策在动态随机设置中实现了这种类型的最优性。 这些结果用于证明贪婪算法在规划一种空中交通管理计划时是最佳的。 我们还提供较弱的条件,可以加强现有政策。 这些结果可以应用于在按需出租车服务中将乘客与司机匹配的问题。 他们指定了乘客和驾驶员不应留下的条件。

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