Ordinary and Prophet Planning Under Uncertainty in Bernoulli Congestion Games
Year: 2024
Type: article
Abstract: Uncertain Demand in Transportation Reduces Worst-Case Congestion In “Ordinary and Prophet Planning Under Uncertainty in Bernoulli Congestion Games,” Cominetti, Scarsini, Schröder, and Stier-Moses characterize the inefficiency introduced by self-minded travelers in congested networks, such as those in big cities. When the likelihood that travelers are present in a congested network is smaller, the uncertainty affects the resulting conditions but also what a social planner would do. Contrary to what might be expected, the consequence is a reduction of the worst-case expressions for the inefficiency of the prevailing traffic conditions with respect to the routes of a social planner. This reduction holds under two possible informational assumptions for the social planner. An ordinary planner only has statistical information based on past data in terms of the expected number of travelers, whereas a prophet planner is informed of the participation outcomes right when travelers start their trips.
Source: Operations Research
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
Awards: ITERATIONS OF NONEXPANSIVE MAPS AND FIRST-ORDER DESCENT METHODS FOR CONVEX OPTIMIZATION, G2599072453, G3456024878, G3826037530, G598502428, ADAPTING TO THE UNCERTAINTIES AND RISKS OF CLIMATE CHANGE ADVANCED METHODS AND MODELS FOR ENERGY SYSTEMS AND MARKETS, ITERATIONS OF NON-EXPANSIVE MAPS AND SUMS OF BERNOULLIS, G972786147
OpenAlex ID: W4401722268