Syllabus
Introduction – linear programming – revised simplex method – duality and sensitivity analysis – dual simplex method – goal programming – integer programming – network optimization models – dynamic programming – nonlinear programming – unconstrained and constrained optimization – nontraditional optimization algorithms.
Text Books
Same as Reference
References
1. Ravindran, A., Phillips, D. T., and Solberg, J. J., Operations Research: Principles and Practice, 2nd ed., John Wiley (2012).
2. Taha, H. A., Operations Research: An Introduction, 9th ed., Prentice Hall of India (2010).
3. Winston, W. L., Operations Research: Applications and Algorithms, 4th ed., Cengage Learning (2010).
4. Rao, S. S., Engineering Optimization: Theory and Practices, 4th ed., John Wiley (2009).
5. Deb, K., Optimization for Engineering Design: Algorithms and Examples, 2nd ed., Prentice Hall of India (2012).
Course Outcomes (COs):
CO1: Apply basic concepts of mathematics to formulate an optimization problem.
CO2: Analyze and solve general linear programming, integer programming and other operations research problems.
CO3: Analyze and solve various constrained and unconstrained non-linear programming problems in single variable as well as multivariable.
CO4: Implement computer codes for mathematical as well non-traditional methods, and analyze the results.