The mathematical science of facility locating has attracted much
attention in d- crete and continuous optimization over nearly last four
decades. Investigators have focused on both algorithms and formulations
in diverse settings in both the private sectors (e.g., industrial
plants, banks, retail facilities, etc.) and the public sectors (e.g.,
hospitals, post stations, etc.). Facility location problems locate a set
of facilities (resources) to minimize the cost ofsatisfying someset
ofdemands(ofthecustomers)with respectto some set of constraints.
Facility location decisions are critical elements in strategic planning
for awiderangeofprivateandpublic?rms.Thebranchesoflocatingfacilities
arebroad and long-lasting, in?uencing numerous operational and
logistical decisions. High costs associated with property acquisition
and facility construction make facility location or relocation projects
long-term investments. Decision makers must select sites that will not
only perform well according to the current system state, but also
willcontinuetobepro?tableforthefacility'slifetime, evenas
environmentalfactors change, populationsshift,
andmarkettrendsevolve.Findingrobustfacilitylocations is thus a dif?cult
task, demanding decision makers to account for uncertain future events.
Locationscience is an areaof analyticalstudythat can be tracedbackto
Pierrede Fermat, Evagelistica Torricelli (a student of Galileo), and
Battista Cavallieri. Each one independently proposed (and some say
solved) the basic Euclidean spatial - dian problem early in the
seventeenth century.
