This course focuses on a class of problemsthat can be modeled as a linear programming model. Formally, a linear programming model is either a minimization or maximization of a linear function of several variables constrained with linear inequalities. Surprisingly , a large number of decision problems fit into this framework. This explains why linear programming is so widely used in a variety of industries, ranging from transportation to health care, from finance to manufacturing. This methodologies development will include the simplex algorithm, theorem of duality, complementary slackness, sensitivity analysis network flows, and network simplex.