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Facility location with economies of scale and congestion

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.

Identiferoai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/5469
Date January 2010
CreatorsLu, Da
Source SetsUniversity of Waterloo Electronic Theses Repository
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation

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