Researchers working with nonlinear programming often claim "the word is
non- linear" indicating that real applications require nonlinear
modeling. The same is true for other areas such as multi-objective
programming (there are always several goals in a real application),
stochastic programming (all data is uncer- tain and therefore stochastic
models should be used), and so forth. In this spirit we claim: The word
is multilevel. In many decision processes there is a hierarchy of
decision makers, and decisions are made at different levels in this
hierarchy. One way to handle such hierar- chies is to focus on one level
and include other levels' behaviors as assumptions. Multilevel
programming is the research area that focuses on the whole hierar- chy
structure. In terms of modeling, the constraint domain associated with a
multilevel programming problem is implicitly determined by a series of
opti- mization problems which must be solved in a predetermined
sequence. If only two levels are considered, we have one leader
(associated with the upper level) and one follower (associated with the
lower level).