A hybrid algorithm for capacitated plant location problem

Authors:
Ming-Che Lai;Han-suk Sohn;Tzu-Liang (Bill) Tseng;Chunkuan Chiang
Affiliations:
Department of Marketing and Logistics Management, Yu Da University, Miao-Li County 361, Taiwan;Department of Industrial Engineering, New Mexico State University, Las Cruces, NM 88003, USA;Department of Industrial Engineering, University of Texas, El Paso, TX, USA;Department of Industrial Engineering, New Mexico State University, Las Cruces, NM 88003, USA
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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Abstract

This paper presents a new hybrid algorithm for a classical capacitated plant location problem. Benders' decomposition algorithm has been successfully applied in many areas. A major difficulty with this decomposition lies in the solution of master problem, which is a ''hard'' problem, costly to compute. Our proposed algorithm, instead of using a costly branch-and-bound method, incorporates a genetic algorithm to obtain ''good'' suboptimal solutions to the master problem at a tremendous saving in the computational effort. The performance of the proposed algorithm is tested on randomly generated data and also well-known existing data. The computational results indicate that the proposed algorithm is effective and efficient for the capacitated plant location problem and competitive with the Benders' decomposition algorithm.