Quantitative Methods in Transportation provides the most useful, simple, and advanced quantitative techniques for solving real-life transportation engineering problems. It aims to help transportation engineers and analysts to predict travel and freight demand, plan new transportation networks, and develop various traffic control strategies that are safer, more cost effective, and greener.
Transportation networks can be exceptionally large, and this makes many transportation problems combinatorial, and the challenges are compounded by the stochastic and independent nature of trip-planners decision making. Methods outlined in this book range from linear programming, multi-attribute decision making, data envelopment analysis, probability theory, and simulation to computer techniques such as genetic algorithms, simulated annealing, tabu search, ant colony optimization, and bee colony optimization. The book is supported with problems and has a solutions manual to aid course instructors.
1. Mathematical programming
2. Optimal paths
3. Multi-attribute decision-making
4. Probability theory
7. Queueing theory
8. Heuristic and metaheuristic algorithms
‘[The book] articulates novel, leading edge quantitative methods that include metaheuristic methods and artificial intelligence applications. These are relatively new in transportation.’
-- David Gillingwater, Loughborough University, UK