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Found 4 papers, 1 papers with code
Contextual Stochastic Vehicle Routing with Time Windows
We study the vehicle routing problem with time windows (VRPTW) and stochastic travel times, in which the decision-maker observes related contextual information, represented as feature variables, before making routing decisions.
Spatial-temporal-demand clustering for solving large-scale vehicle routing problems with time windows
Pruning is based on customers' similarity information obtained in the decomposition phase.
Bilevel Optimization for Feature Selection in the Data-Driven Newsvendor Problem
The lower-level problem learns the optimal coefficients of the decision function on a training set, using only the features selected by the upper-level.
Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management
Bike-sharing systems are a rapidly developing mode of transportation and provide an efficient alternative to passive, motorized personal mobility.
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