Location Science is rooted in the literature of location analysis that started with the works of von Thunen (1826) in terms of land-use allocation and Launhardt (1872) and Weber (1909) in terms of industrial location. Heuristics are usually developed to solve problems that are unusually hard to solve or to solve problems in a faster and more efficient manner, while sacrificing the prospect of guaranteeing an optimal result. Heuristic, an approach that is designed to provide a feasible solution to a problem with no guarantee as to whether the solution is optimal or even close to optimal. The traveling salesman problem is a member of this class of problems. NP-hard, a class of problems in NP that are considered to be at least as hard as the hardest to solve problems in the class NP. Such models are considerably more difficult to solve than LPs and, in most cases, involve computational complexities that are classified as NP. Integer-linear programming (ILP) problem: an LP with additional integer-value restrictions on some or all of the variables. It is more likely that worst case instances of such problems are only solvable in exponential time. NP (non-deterministic polynomial), a class of problems that is not considered to be solvable in polynomial time as a function of problem parameters. Such problems can be solved in polynomial time (as a function of problem parameters). Such models can be very large, involving more than a million constraints and variables. It is comprised of an objective function whose value is to be optimized and a set of equality and inequality constraints. Linear programming (LP) problem: a model consisting of continuous variables (often constrained to be non-negative in sign) and linear terms.
Using the p-median model in solving other location problems.
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