Approximation algorithm for the two-stage stochastic set multicover problem with simple resource

We study a two-stage, finite-scenarios stochastic version of the set multicover problem, where there is uncertainty about a demand for each element to be covered and the penalty cost is imposed linearly on the shortfall in each demand. This problem is NP-hard and has an application in shift scheduling in crowdsourced delivery services. For this … Read more

Increasing Driver Flexibility through Personalized Menus and Incentives in Ridesharing and Crowdsourced Delivery Platforms

Allowing drivers to choose which requests to fulfill provides drivers with much-needed autonomy in ridesharing and crowdsourced delivery platforms. While stochastic, a driver’s acceptance of requests in their menu is influenced by the platform’s offered compensation. Therefore, in this work, we create and solve an optimization model to determine personalized menus and incentives to offer … Read more

Optimizing Driver Menus Under Stochastic Selection Behavior for Ridesharing and Crowdsourced Delivery

Peer-to-peer logistics platforms coordinate independent drivers to fulfill requests for last mile delivery and ridesharing. To balance demand-side performance with driver autonomy, a new methodology is created to provide drivers with a small but personalized menu of requests to choose from. This creates a Stackelberg game, in which the platform leads by deciding what menu … Read more