Facility location problem
Authors: Liz Cantlebary, Lawrence Li (CHEME 6800 Fall 2020)
Stewards: Allen Yang, Fengqi You
The Facility Location Problem (FLP) is a classic optimization problem that determines the best location for a factory or warehouse to be placed based on geographical demands, facility costs, and transportation distances. These problems generally aim to maximize the supplier's profit based on the given customer demand and location. FLP can be further broken down into capacitated and uncapacitated problems, depending on whether the facilities in question have a maximum capacity or not.
Theory and Formulation
The Weber Problem is a simple FLP that consists of locating the geometric median between three points with different weights. The geometric median is a point between three given points in space such that the sum of the distances between the median and the other three points is minimized. It is based on the premise of minimizing transportation costs from one point to various destinations, where each destination has a different associated cost per unit distance.
Given points on a plane with associated weights , the 2-dimensional Weber problem to find the geometric median is formulated as(1)
Capacitated and Uncapacitated FLPs
A capacitated facility problem applies constraints to the production and transportation capacity of each facility. As a result, customers may not be supplied by the most immediate facility, since this facility may not be able to satisfy the given customer demand.
In a problem with facilities and customers, the capacitated formulation defines a binary variable and a variable for each facility and each customer . If facility is open, ; otherwise . Open facilities have an associated fixed cost and a maximum capacity . is the fraction of the total demand of customer that facility has satisfied and the transportation cost between facility and customer is represented as . The capacitated FLP is therefore defined as
In an uncapacitated facility problem, the amount of product each facility can produce and transport is assumed to be unlimited, and the optimal solution results in customers being supplied by the lowest-cost, and usually the nearest, facility. Using the above formulation, the unlimited capacity means can be assumed to be a sufficiently large constant, while is now a binary variable, because the demand of each customer can be fully met with the nearest facility. If facility supplies customer , then ; otherwise .