Abstract
In this paper, a new genetic mating scheme called Controlled Content Crossover (CCC) is proposed and applied to solve the optical network component allocation problem. In order to solve the constrained optimization problem, CCC finds the selected set of the components with the minimum cost while it keeps the total dispersion value of the answer within a double-sided limit. The simulation results show that CCC finds the optimum answer matching closely with CPLEX solution.
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References
Goldberg, D.E.: Genetic algorithms in search, optimization, and machine learning. Addison-Wesley Pub. Co., Reading (1989)
Chu, P.C., Beasley, J.E.: A Genetic Algorithm for Multidimentional Knapsack Problem. Journal of Heuristics 4, 63–86 (1998)
Dallaali, M.A., Premaratne, M.: Configuration of optical network using Genetic Algorithm. In: Proceeding of ONDM 2004, pp. 279–292 (2004)
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© 2004 Springer-Verlag Berlin Heidelberg
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Dallaali, M.A., Premaratne, M. (2004). Controlled Content Crossover: A New Crossover Scheme and Its Application to Optical Network Component Allocation Problem. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_37
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DOI: https://doi.org/10.1007/978-3-540-24855-2_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22343-6
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