CE5972

Optimisation Techniques in Transportation Engineering

Objectives:

  1. To develop fundamental understanding of different optimisation techniques applied in transportation engineering.
  2. To model complex transportation problems and solve them using suitable optimisation methods.
  3. To interpret solutions derived from optimisation models and make informed managerial decisions in real-world transportation scenarios.

Course Content:

  1. Linear programming: Principles of linear programming including the formulation of the objective function, decision variables, and constraints within the context of transportation engineering; graphical method and simplex algorithm; sensitivity analysis and duality; inferring results and making decisions.
  2. Non-linear programming: Principles of non-linear programming and associated solution methods including local search heuristics, evolutionary computation techniques, and swarm intelligence algorithms.
  3. Transportation Engineering problems: Variants of transportation problem, assignment problem, trans-shipment problem, least-cost path problem, traveling salesman problem, vehicle routing problem, facility location problem, and network design problem.

Textbooks:

  1. Hillier, F. S., & Lieberman, G. J. (2024). Introduction to operations research. (12th edition). McGraw-Hill.
  2. Winston, W. L. (2022). Operations Research: Applications and Algorithms. (4th edition). Cengage Learning.
  3. Al-Khateeb, G. (2020). Solved Practical Problems in Transportation Engineering. (1st edition). Taylor & Francis Group.

Reference Books:

  1. Taha, H. A. (2022). Operations Research: An Introduction. (11th edition). Pearson Education India.
  2. Balakrishnan, N., Render, B., & Stair, R. M. (2013). Managerial decision modelling with spreadsheets. (3rd edition). Prentice Hall Press.