IN THIS CHAPTER
Discovering how optimization happens using linear programming
Transforming real-world problems into math and geometry ones
Learning how to use Python to solve linear programming problems
Linear programming made a first appearance during World War II when logistics proved critical in maneuvering armies of millions of soldiers, weapons, and supplies across geographically variegated battlefields. Tanks and airplanes needed to refuel and rearm, which required a massive organizational effort to succeed in spite of limitations in time, resources, and actions from the enemy.
You can express most of these military problems in mathematical form. Mathematician George Bernard Dantzig, who was employed in the U.S. Air Force Office of Statistical Control, devised a smart way to solve these problems using the simplex algorithm. Simplex is the core idea that created interest in numerical optimization after the war and gave birth to the promising field of linear programming. The availability of the first performing computers of the time also increased interest, rendering complex computations solvable in a new and fast way. You can view the ...