ABSTRACT

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.

chapter 1|76 pages

Mathematical programming

chapter 2|24 pages

Optimal paths

chapter 3|50 pages

Multi-attribute decision-making

chapter 4|56 pages

Probability theory

chapter 5|94 pages

Statistics

chapter 6|22 pages

Simulation

chapter 7|30 pages

Queueing theory

chapter 8|102 pages

Heuristic and metaheuristic algorithms