Based on the plethora of advancements in optimization algorithms and computer technology that has occurred in the past 50 years - is Linear Programming today as "Powerful" and "Indispensable" as it was in the past?
Are there still some problems that can only be solved using Linear Programming Methods? Do we continue to teach and learn about Linear Programming for only for it's historical importance and basis/introduction to help in understanding modern optimization methods (e.g. "a stepping stone") - or is that in certain types of problems, methods from Linear Programming style display some "attractive theoretical properties" (e.g. convergence), even in the face of modern optimization methods such as Quasi-Newton Methods, Stochastic Gradient Descent and Evolutionary Algorithms?
Even today, are there some problems that can be ONLY solved using methods from Linear Programming?