Linear Programming 27: Optimality is no harder than feasibility

Linear Programming 27: Optimality is no harder than feasibility Abstract: We give a third explanation for why finding an optimal solutions is no harder than finding a feasible solution, using the duality of linear programming. This video accompanies the class "Linear Programming and Network Flows" at Colorado State University https://www.math.colostate.edu/~adams/teaching/math510fall2020/ We are following the book "Understanding and Using Linear Programming" by Jirí Matoušek and Bernd Gärtner https://link.springer.com/book/10.1007/978-3-540-30717-4 Our course notes are available at https://www.math.colostate.edu/~adams/teaching/math510fall2020/LinearProgrammingNotes.pdf