Facility location with economies of scale and congestion
Loading...
Files
Date
2010-09-01T18:25:02Z
Authors
Lu, Da
Advisor
Journal Title
Journal ISSN
Volume Title
Publisher
University of Waterloo
Abstract
Most literature on facility location assumes a fixed set-up cost and a linear variable cost. However, as production volume increases, cost savings are achieved through economies of scale, and then when production exceeds a certain capacity level, congestion occurs and costs start to increase significantly. This leads to an S-shaped cost function that makes the location-allocation decisions challenging. This thesis presents a nonlinear mixed integer programming formulation for the facility location problem with economies of scale and congestion and proposes a Lagrangian solution approach. Testing on a variety of functions and cost settings reveals the efficiency of the proposed approach in finding solutions that are within an average gap of 3.79% from optimal.