Introduction – linear programming – duality and sensitivity analysis – transportation and assignment problems – goal programming – integer programming – network optimization models – dynamic programming – theory of games – queuing theory – simulation – nontraditional optimization algorithms.

1. Taha, H. A., Operations Research: An introduction, 9th ed., Pearson (2010).

1. Ravindran, A., Phillips, D. T., and Solberg, J. J., Operations Research: Principles and Practice, 2nd ed., Wiley-India (2006).

2. Winston, W. L., Operations Research: Applications and Algorithms, 4th ed., Cengage Learning (2010).

3. Sharma, J. K., Operations Research: Theory and Applications, 4th ed., Macmillan Publishers (2009).

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.