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UNIVERSITY OF KERALA - College of Engineering, Trivandrum

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08.806.13. Elective V. SYSTEMS ENGINEERING<br />

FOR CIVIL ENGINEERS<br />

L T P/D Cr<br />

3 0 0 3<br />

Module I<br />

Systems engineering- System-definition and examples <strong>of</strong> civil engineering systems, system analysis, system<br />

design and system synthesis. Steps in analysis <strong>of</strong> systems- Mathematical modeling <strong>of</strong> systems- Optimization<br />

problems-Objective function and constraints.<br />

Formulation <strong>of</strong> the following optimization problems for civil engineers-minimum weight design <strong>of</strong> trusses and<br />

frames, minimum cost design <strong>of</strong> beams, Column design based on Euler’s theory <strong>of</strong> buckling load, Optimal<br />

design <strong>of</strong> water distribution systems, single reservoir operation, Minimum cost design <strong>of</strong> lined irrigation canals.<br />

Traffic signal time optimization, Effluent disposal to rivers.<br />

Concavity and convexity <strong>of</strong> optimization problems- Solution <strong>of</strong> single variable optimization problems-Calculus<br />

based methods, Newton, bisection and secant method<br />

Module- II<br />

Solution <strong>of</strong> multi variable optimization problems- Lagrange multiplier method-KKT conditions. Unconstrained<br />

optimization techniques for multi variable problems-direct search methods, Random search, uni-variate and<br />

pattern search-Hook and Jeeve’s method, Descent methods-Fletcher and reeves method, Quasi-Newton methods<br />

(conceptual idea only),<br />

Constrained optimization and constraint handling - penalty function approach (conceptual idea only).<br />

Module- III<br />

Dynamic programming (DP) - Bellman’s principle <strong>of</strong> optimality, Application <strong>of</strong> DP to a pipe network problem.<br />

Basic ideas <strong>of</strong> integer programming and multi-objective optimization (Descriptions only).<br />

Evolutionary algorithms for optimization- Basic principles <strong>of</strong> Genetic Algorithms, Simulated Annealing and<br />

Swarm Intelligence Techniques (Ant colony optimization and particle swarm optimization) (conceptual ideas<br />

only).<br />

Simulation-Concept <strong>of</strong> Monte Carlo Simulation (No numerical problem).<br />

References/ Text Books<br />

1. Fox R L -Optimization methods for engineering design – Weily<br />

2. Rao S S -<strong>Engineering</strong> Optimization-theory and practice-, New Age International<br />

3. Belegundu and Chandrapatla-Optimization concepts and applications in engineering-, Prentice Hall<br />

India Ltd<br />

4. Deb K -Optimization for engineering design- Algorithms and Examples–, Prentice Hall India Ltd<br />

5. Haftka R T and Gurdal Z -Elements <strong>of</strong> structural optimization-Springer<br />

6. Goldberg DE-Genetic Algorithms in search, optimization and machine learning.<br />

7. Engelbrecht A P -Fundamentals <strong>of</strong> computational swarm Intelligence- Weily<br />

8. Kennedy J and Eberhart R C-Swarm Intelligence- Morgan Kaufaman<br />

9. Arora J S-Introduction to optimum design- Elsevier<br />

10. Vedula P and Mujumdar P P-Water resources systems- TMH<br />

Question paper: Duration: 3 Hrs<br />

The question paper consists <strong>of</strong> part A and part B.<br />

Part A consist <strong>of</strong> 8 questions <strong>of</strong> 5 marks each. Candidate has to answer all questions.<br />

Part B is for 60 marks. Part B is divided into three modules. Candidate has to answer one full question out<br />

<strong>of</strong> two, from each module.<br />

Note: At least one assignment should be computer oriented. The candidate should practice to solve simple<br />

optimization problems from civil engineering field using any commercial s<strong>of</strong>tware.<br />

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