Lecture
This lecture covers the local sensitivity analysis for linear programming problems, focusing on changes in the constraint matrix and objective function coefficients. The instructor explains how to determine if the current basis remains optimal when there are local changes in the problem. Various scenarios are explored, such as changes in the right-hand side values and the addition of new variables or constraints. The lecture also delves into the implications of these changes on the feasibility and optimality conditions of the linear programming model, providing insights into how to adapt the solution without starting from scratch.