At first sight discrete and fractional programming techniques appear to
be two com- pletely unrelated fields in operations research. We will
show how techniques in both fields can be applied separately and in a
combined form to particular models in location analysis. Location
analysis deals with the problem of deciding where to locate facilities,
con- sidering the clients to be served, in such a way that a certain
criterion is optimized. The term "facilities" immediately suggests
factories, warehouses, schools, etc., while the term "clients" refers to
depots, retail units, students, etc. Three basic classes can be
identified in location analysis: continuous location, network location
and dis- crete location. The differences between these fields arise from
the structure of the set of possible locations for the facilities.
Hence, locating facilities in the plane or in another continuous space
corresponds to a continuous location model while finding optimal
facility locations on the edges or vertices of a network corresponds to
a net- work location model. Finally, if the possible set of locations is
a finite set of points we have a discrete location model. Each of these
fields has been actively studied, arousing intense discussion on the
advantages and disadvantages of each of them. The usual requirement that
every point in the plane or on the network must be a candidate location
point, is one of the mostly used arguments "against" continuous and
network location models.