Applications of Heuristic Algorithms to Optimal Road Congestion Pricing

This book proposes a method for dynamic pricing for high-occupancy toll (HOT) lanes using non-linear programming techniques, finite difference stochastic approximation, genetic algorithms, and simulated annealing stochastic algorithms. It aims to optimize flow and toll to minimize travel time and reduce congestion, with ANOVA results and econometric forecasting methods. Case studies from around the world are presented.

Format: Hardback
Length: 142 pages
Publication date: 04 October 2023
Publisher: Taylor & Francis Ltd

Road congestion poses significant financial, social, and environmental burdens. One potential solution is the implementation of high-occupancy toll (HOT) lanes, which allow for the separation of traffic and the charging of a fee for using these lanes. This book offers a comprehensive approach to dynamic pricing for HOT lanes, employing non-linear programming (NLP) techniques, finite difference stochastic approximation, genetic algorithms, and simulated annealing stochastic algorithms within a cell transmission framework. The objective is to optimize flow and toll rates to minimize total travel time and alleviate congestion.

To evaluate the effectiveness of the proposed algorithms, ANOVA results are presented, highlighting differences in their performance in solving the problem and reducing travel time. Additionally, econometric forecasting methods utilizing vector autoregressive techniques are demonstrated to accurately predict demand.

The book compares various optimization approaches and showcases case studies from around the world, including the I-95 Express HOT Lane in Miami, USA. It serves as a valuable resource for transportation practitioners and researchers seeking to enhance road congestion pricing strategies.

Weight: 439g
Dimension: 216 x 138 (mm)
ISBN-13: 9781032415659