Discrete optimization is a branch of optimization in applied mathematics and computer science.
As opposed to continuous optimization, the variables used in the mathematical program (or some of them) are restricted to assume only discrete values, such as the integers.
Two notable branches of discrete optimization are:
- combinatorial optimization, which refers to problems on graphs, matroids and other discrete structures
- integer programming
These branches are closely intertwined however since many combinatorial optimization problems can be modeled as integer programs (e.g. shortest path) and conversely, integer programs can often be given a combinatorial interpretation.
Famous quotes containing the word discrete:
“We have good reason to believe that memories of early childhood do not persist in consciousness because of the absence or fragmentary character of language covering this period. Words serve as fixatives for mental images. . . . Even at the end of the second year of life when word tags exist for a number of objects in the child’s life, these words are discrete and do not yet bind together the parts of an experience or organize them in a way that can produce a coherent memory.”
—Selma H. Fraiberg (20th century)