Road congestion imposes major financial, social, and environmental costs. One solution is the operation of high-occupancy toll (HOT) lanes. This book outlines a method for dynamic pricing for HOT lanes based on non-linear programming (NLP) techniques, finite difference stochastic approximation, genetic algorithms, and simulated annealing stochastic algorithms, working within a cell transmission framework. The result is a solution for optimal flow and optimal toll to minimize total travel time and reduce congestion.
ANOVA results are presented which show differences in the performance of the NLP algorithms in solving this problem and reducing travel time, and econometric forecasting methods utilizing vector autoregressive techniques are shown to successfully forecast demand.
- The book compares different optimization approaches
- It presents case studies from around the world, such as the I-95 Express HOT Lane in Miami, USA
Applications of Heuristic Algorithms to Optimal Road Congestion Pricing is ideal for transportation practitioners and researchers.
Payez facilement par carte, Klarna, Apple Pay ou Google Pay. Pas satisfait ? Vous avez toujours une garantie de remboursement de 14 jours. En savoir plus dans nos conditions. Si vous avez des questions, envoyez-nous un e-mail à hello@memmo.org.
Memmo facilite tes études, où que tu sois dans le monde. On rassemble tes manuels de cours et des outils d'étude intelligents au même endroit : résumés, quiz, podcasts et flashcards. Et il y a Ted, ton compagnon d'étude qui répond à toutes tes questions. Plus de 50 000 étudiants étudient déjà ici – conçu pour t'aider à apprendre plus vite et à moins stresser.