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Integrated genetic algorithm and goal programming for network topology design problem with multiple objectives and multiple criteria

Published: 01 June 2008 Publication History

Abstract

Network topology design (NTD) with multiple objectives has been presented by many researchers. However, no work in the literature has addressed this issue with both multiple objectives and multiple criteria. In order to suit real-world situations, this paper presents a new idea integrating genetic algorithm and goal programming to establish a model for solving the NTD problem with multiple objectives and multiple criteria taken into consideration. In addition, the proposed model can also solve both construct and extend network topology problems under shared risk link group (SRLG) constraints. Finally, illustrative examples are included to demonstrate the superiority and usefulness of the proposed method.

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  • (2010)Grids-Based Data Parallel Computing for Learning Optimization in a Networked Learning Control SystemsProceedings, Part I, of the International Conference on Life System Modeling and Intelligent Computing - Volume 632810.1007/978-3-642-15621-2_26(221-232)Online publication date: 17-Sep-2010

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Published In

cover image IEEE/ACM Transactions on Networking
IEEE/ACM Transactions on Networking  Volume 16, Issue 3
June 2008
249 pages

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IEEE Press

Publication History

Published: 01 June 2008
Published in TON Volume 16, Issue 3

Author Tags

  1. genetic algorithm (GA)
  2. goal programming
  3. network topology design (NTD)

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  • (2010)Grids-based data parallel computing for learning optimization in a networked learning control systemsProceedings of the 2010 international conference on Life system modeling and and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part I10.5555/1888466.1888494(221-232)Online publication date: 17-Sep-2010
  • (2010)Grids-Based Data Parallel Computing for Learning Optimization in a Networked Learning Control SystemsProceedings, Part I, of the International Conference on Life System Modeling and Intelligent Computing - Volume 632810.1007/978-3-642-15621-2_26(221-232)Online publication date: 17-Sep-2010

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