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Controlled Content Crossover: A New Crossover Scheme and Its Application to Optical Network Component Allocation Problem

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Book cover Genetic and Evolutionary Computation – GECCO 2004 (GECCO 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3103))

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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

  1. Goldberg, D.E.: Genetic algorithms in search, optimization, and machine learning. Addison-Wesley Pub. Co., Reading (1989)

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  2. Chu, P.C., Beasley, J.E.: A Genetic Algorithm for Multidimentional Knapsack Problem. Journal of Heuristics 4, 63–86 (1998)

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  3. 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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Author information

Authors and Affiliations

  1. Advanced Computing and Simulation Laboratory (AXL), Department of Electrical and Computer System Engineering, Monash University, P.O. Box: 35, Clayton, Victoria, 3800, Australia

    Mohammad Amin Dallaali & Malin Premaratne

Authors
  1. Mohammad Amin Dallaali
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  2. Malin Premaratne
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Editor information

Editors and Affiliations

  1. Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), Kanpur, 208016, Uttar Pradesh, India

    Kalyanmoy Deb

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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

  • Online ISBN: 978-3-540-24855-2

  • eBook Packages: Springer Book Archive

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