Syllabus

Module I:
Introduction. Need for engineering optimal design. Optimum design formulation: Decision variable, objective function and constraints. unconstrained optimization methods. [4 hrs.]
Module II:
Single variable optimization methods: Region elimination method – Golden section search, Interval halving method Gradient based method – Newton-Raphson, bisection and secant method. [4 hrs.]
Module III:
Multi variable optimization methods: Direct search method - (Hooke-Jeeve) pattern search, simplex reflection search, Powell’s conjugate direction search. Gradient Based methods: Cauchy’s steeped descent, Newton’s method, Levenberg-Marquardt’s method, Fletcher- Reeve method. [6 hrs.]
Module IV:
Constrained optimization methods: Kuhn Tucker condition, Penalty function method, Augmented Lagrangian method, sequential unconstrained minimization, cutting plane method. [6 hrs.]
Module V:
Introduction to Evolutionary algorithms. Need for evolutionary algorithms. Type of evolutionary methods. Introduction to Genetic algorithm (GA). Difference and similarities between GA and traditional methods. Basic operations of GA: reproduction, crossover, mutation and elitism. Binary coded and Real coded GA. [8 hrs.]
Module VI:
Application of Optimization techniques: Water resource planning management, Structural Optimization, Transportation planning and Management, Slope stability and optimal dimensioning of foundations. Multi-objective optimization models. [8 hrs.]

Civil Engineering design

Finding approximate and practical solution to complicated Civil Engineering problems

Decision on various design elements

carry out investigations of complex problems

After completion of the course, students will be able to:
CO1: Apply knowledge of Optimization in Civil Engineering problems.
CO2: Assess the Optimization Parameters, like, Decision variable, Objective function and Constraints.
CO3: Evaluate different optimization methods.
CO4: Apply knowledge of Evolutionary algorithms, like, Genetic algorithm (GA) to various real-life problems.
CO5: Apply Optimization techniques in Civil Engineering problems.

J.S. Arora, Introduction to Optimum Design, Elsevier

K. Deb, Optimization for Engineering. Design: Algorithms & Examples, Prentice Hall India

K. Deb, Multi-Objective Optimization using Evolutionary Algorithms, John Wiley & Sons

H.A. Taha, Operations Research, Prentice Hall of India