1
Department of Civil Engineering,Iran University of Science and Technology
2
Department of Engineering,Building and Housing Research Center
Abstract
There are various engineering applications dealing with the prototype problem of nding the
best p-medians in a weighted graph. However, the heuristic developments are still of concern due to their
complexity. This paper utilizes genetic algorithm as a well-known reliable evolutionary search for such
a purpose. Problem formulation is studied, introducing a characteristic graph and specialized genotype
representation called Direct Index Coding". The genetic operators are also modi ed due to problem
requirements, and further tuned using a simulated annealing approach. Such an enhanced evolutionary
search tool is then applied to a number of examples to show its e ectiveness regarding the exact results,
and to compare eciency between tuned and non-tuned GA.
Kaveh, A., Shahrouzi, M., & Naserifar, Y. (2010). Tuned Genetic Algorithms for Finding p-Medians of a Weighted Graph. (e3161). Scientia Iranica, 17(5), e3161
MLA
Kaveh, A., Shahrouzi, M., & Naserifar, Y. "Tuned Genetic Algorithms for Finding p-Medians of a Weighted Graph" .e3161 , Scientia Iranica, 17, 5, 2010, e3161.
HARVARD
Kaveh A., Shahrouzi M., Naserifar Y. (2010). 'Tuned Genetic Algorithms for Finding p-Medians of a Weighted Graph', Scientia Iranica, 17(5), e3161.
CHICAGO
A. Kaveh, M. Shahrouzi & Y. Naserifar, "Tuned Genetic Algorithms for Finding p-Medians of a Weighted Graph," Scientia Iranica, 17 5 (2010): e3161,
VANCOUVER
Kaveh A., Shahrouzi M., Naserifar Y. Tuned Genetic Algorithms for Finding p-Medians of a Weighted Graph. Scientia Iranica. 2010;17(5):e3161.
