The Optimization of the Bandpass Lengths in the Multi-Bandpass Problem

  • Mehmet Kurt
  • Hakan Kutucu
  • Arif Gursoy
  • Urfat Nuriyev
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 241)


The Bandpass problem has applications to provide a cost reduction in design and operating telecommunication network. Given a binary matrix Am × n and a positive integer B called the Bandpass length, a set of B consecutive non-zero elements in any column is called a Bandpass. No two bandpasses in the same column can have common rows. The general Bandpass Problem consists of finding an optimal permutation of rows of the matrix A that produces the maximum total number of bandpasses having the same given bandpass length B in all columns. The Multi- Bandpass problem includes different bandpass lengths Bj in each column j of the matrix A, where j = 1,2,…,n. In this paper, we propose an extended formulation for the Multi-Bandpass problem. A given Bj may not be always efficient bandpass lengths for the communication network. Therefore, it is important to find an optimal values of the bandpass lengths in the Multi-Bandpass problem. In this approach, the lengths in each destination are defined as z j and we present a model to find the optimal values of z j. Then, we calculate the approximate solution of this model using genetic algorithm for the problem instances which are presented in an online library.


Combinatorial optimization Bandpass problem Telecommunication Genetic algorithm 


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The work is supported by the Key Program of National Natural Science Foundation of China (Grant No. 70831005), also supported by “985” Program of Sichuan University (Innovative Research Base for Economic Development and Management), and also supported by Philosophy and Social Sciences Planning Project of Sichuan Province (Grant No. SC12BJ05).


  1. 1.
    Al-Jabari M, Sawalha H (2002) Treating stone cutting waste by flocculation-sedimentation. In: Proceedings of the Sustainable Environmental Sanitation and Water Services Conference, 28th WEDC Conference, Calcutta, IndiaGoogle Scholar
  2. 2.
    Nasserdine K, Mimi Z, Bevan B et al (2009) Environmental management of the stone cutting industry. Journal of Environmental Management 90(1):466–470Google Scholar
  3. 3.
    Almeida N, Branco F, Santos J (2007) Recycling of stone slurry in industrial activities: Application to concrete mixtures. Building and Environment 42(2):810–819Google Scholar
  4. 4.
    Buffa E, Miller J (1979) Production-Inventory Systems: Planning and control. Richard D. Irwin Homewood, ILGoogle Scholar
  5. 5.
    Lewis CD (1981) Scientific inventory control. ButterworthsGoogle Scholar
  6. 6.
    Xu J, Liu Y (2008) Multi-objective decision making model under fuzzy random environment and its application to inventory problems. Information Sciences 178(14):2899–2914Google Scholar
  7. 7.
    Xu J, Zhou X (2011) Fuzzy-like multiple objeictive decision making. SpringerGoogle Scholar
  8. 8.
    Xu J, Yao L (2009) A class of multiobjective linear programming models with random rough coefficients. Mathematical and Computer Modelling 49(1-2):189–206Google Scholar
  9. 9.
    Xu J, Yao L, Zhao X (2011) A multi-objective chance-constrained network optimal model with random fuzzy coefficients and its application to logistics distribution center location problem. Fuzzy Optimization and Decision Making 10(3):255–285Google Scholar
  10. 10.
    Yao L, Xu J (2013) A class of expected value bi-level programming problems with random coefficients based on rough approximation and its application to a production-inventory system. Abstract and Applied Analysis (In press)Google Scholar
  11. 11.
    Yao L, Xu J (2012) A stone resource assignment model under the fuzzy environment. Mathematical Problems in Engineering doi: 10.1155/2012/265837
  12. 12.
    Gen M, Cheng R (1997) Genetic algorithms and engineering design. Wiley- InterscienceGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Mehmet Kurt
    • 1
  • Hakan Kutucu
    • 2
  • Arif Gursoy
    • 3
  • Urfat Nuriyev
    • 3
  1. 1.Department of Mathematics and Computer ScienceIzmir UniversityIzmirTurkey
  2. 2.Department of Computer EngineeringKarabuk UniversityKarabukTurkey
  3. 3.Department of MathematicsEge UniversityIzmirTurkey

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