  The colorful Carath\'eodory theorem, proved by B\'ar\'any in 1982, states
that given d+1 sets of points S_1,...,S_{d+1} in R^d, with each S_i containing
0 in its convex hull, there exists a subset T of the union of the S_i's
containing 0 in its convex hull and such that T contains at most one point from
each S_i. An intriguing question -- still open -- is whether such a set T,
whose existence is ensured, can be found in polynomial time. In 1997,
B\'ar\'any and Onn defined colorful linear programming as algorithmic questions
related to the colorful Carath\'eodory theorem. The question we just mentioned
comes under colorful linear programming.
  The traditional applications of colorful linear programming lie in discrete
geometry. In this paper, we study its relations with other areas, such as game
theory, operations research, and combinatorics. Regarding game theory, we prove
that computing a Nash equilibrium in a bimatrix game is a colorful linear
programming problem. We also formulate an optimization problem for colorful
linear programming and show that as for usual linear programming, deciding and
optimizing are computationally equivalent. We discuss then a colorful version
of Dantzig's diet problem. We also propose a variant of the B\'ar\'any
algorithm, which is an algorithm computing a set T whose existence is ensured
by the colorful Carath\'eodory theorem. Our algorithm makes a clear connection
with the simplex algorithm and we discuss its computational efficiency. Related
complexity and combinatorial results are also provided.
