George Dantzig

Developed by George Dantzig in 1947, the simplex algorithm solves linear programming problems by moving along the edges of a convex polyhedron — the feasible region — to find the optimal vertex. Despite exponential worst-case time complexity, it performs remarkably well in practice and remains one of the most widely used optimization algorithms in industry.

As a graduate student at UC Berkeley in 1939, Dantzig arrived late to a statistics class taught by Jerzy Neyman and copied two problems from the blackboard, assuming they were homework. He solved them and handed them in days later, only to learn they were actually famous unsolved problems in statistics — an incident that later inspired a scene in the film 'Good Will Hunting.'

Dantzig developed linear programming while working as a mathematical advisor for the US Air Force, where he needed to formalize large-scale planning problems such as deployment schedules and resource allocation. The simplex algorithm allowed the military to solve optimization problems that were previously intractable, and his methods were later adopted across industry for oil refining, airline scheduling, and manufacturing.

Dantzig received the National Medal of Science in 1975 from President Gerald Ford for inventing linear programming and the simplex method. He was elected to the National Academy of Sciences and received the John von Neumann Theory Prize from the Operations Research Society of America.