Facility location problem pdf

A BI-OBJECTIVE FACILITY LOCATION PROBLEM IN THE PRESENCE OF A PROBABILISTIC LINE BARRIER Mehdi Amiri-Aref 1, Armand Baboli 2, Nikbakhsh Javadian 1,Reza Tavakkoli-Moghaddam 3 1 Department of Industrial Engineering, Mazandaran University of Science & Technology, Babol, Iran {m.a.aref, nijavadian}@ustmb.ac.ir strategic nature of facility location problems by modeling either stochastic or dynamic problem charac-teristics. Our goal in writing this paper is to provide an overview of facility location research which, through the consideration of time and uncertainty, has helped to move us toward solving more realistic problem instances. Location-Allocation Optimization of Supply . Chain Distribution Networks: A Case Study . Mark Helberg . A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of . Master of Science . Charles R. Harrell, Chair Michael P. Miles Alan J. Boardman . School of Technology . Brigham 2. The ?xed charge facility location problem The ?xed charge facility location problem is a classical location prob-lem and forms the basis of many of the location models that have been used in supply chain design. The problem can be stated simply as fol-lows. We are given a set of customer locations with known demands bl. When each potential facility has a capacity, which is the maximum demand that it can supply, the problem is known as the capacitated~facility l 9cation problem. When the capacity hypothesis is not needed, we have the sinpleor uncaoacitated facility location problem, whichy6 abbreviate by UL. In this paper we address the clinic location selection problem for a fully integrated Sexual Health Service across Hampshire. The service provides outpatient services for Genito-Urinary Medicine, contraceptive and reproductive health, sexual health promotion and a sexual assault referral centre. facility location problems is the paper of Mettu and Plax-ton[11] in which thelocations ofthe demandsare all known ahead of time but the number of facilities to be placed in-creases incrementally in an online fashion. This contrasts with our problem, in which the demands themselves arrive online and we are allowed to open as many facilities as we facility location problem and its generalizations. The main idea of this section is to show the useful relationship between facility location models and pseudo{Boolean functions. In Section 2 we introduce some simple neighborhoods and discuss the relations between local optima and classical Karush{Kuhn{Tucker conditions. We discuss the connection between facility location prob-lems and covering problems, and present approaches to solving facility location problems by reducing them to cov-ering problems. The maximal covering location problem seeks the maximum population which can be served within a stated service distance or time given a limited number of facilities. Defined on a network of nodes and arcs, a mathematical formulation of this problem can be stated as follows: I. Maximize S.T. z = ~ a~y~ Undesirable and semi-desirable facility location problems, because of the contrasting nature of their models, have seen most efforts among bi-objective facility location problems. And in most cases, the objectives are reducing cost as well as the undesirable effects. 2.2 Dynamic Facility Location Problem Closely related to the problem of relocating a mobile inventory for responding to disasters over time is the strea