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A hybrid Hopfield network-genetic algorithm approach for the terminal assignment problem.

Sancho Salcedo-Sanz1, Xin Yao

  • 1School of Computer Science of the University of Birmingham, Edgbaston, Birmingham B15 2TT, UK. sancho@tsc.uc3m.es

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|December 29, 2004
PubMed
Summary

This study introduces a hybrid Hopfield network-genetic algorithm (GA) for the terminal assignment (TA) problem. It effectively finds minimum cost communication networks even when individual assignment costs are unknown, outperforming prior methods.

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Area of Science:

  • Computer Science
  • Operations Research
  • Artificial Intelligence

Background:

  • The terminal assignment (TA) problem seeks to minimize costs when connecting terminals to concentrators for communication networks.
  • Existing methods often fail when individual assignment costs are unknown, relying only on feasible solution costs.
  • Greedy heuristics are inadequate in scenarios with unknown single assignment costs.

Purpose of the Study:

  • To develop a novel hybrid approach for the terminal assignment problem.
  • To address limitations of previous methods in scenarios with unknown individual assignment costs.
  • To demonstrate the algorithm's effectiveness in achieving feasible and cost-efficient solutions.

Main Methods:

  • A hybrid model combining a Hopfield neural network (HNN) and a genetic algorithm (GA).

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  • The HNN manages problem constraints, while the GA optimizes for minimum cost solutions.
  • The approach is designed to handle cases where only the cost of complete feasible solutions is known.

    • Main Results:

    • The hybrid Hopfield network-genetic algorithm successfully achieves feasible solutions for the TA problem.
    • The proposed method outperforms previous approaches, particularly in instances where single assignment costs are not predetermined.
    • Demonstrated applicability to variations of the terminal assignment problem.

    Conclusions:

    • The hybrid HNN-GA is a robust method for solving the terminal assignment problem, especially under complex cost conditions.
    • This approach offers a significant improvement over existing algorithms for TA when individual costs are unknown.
    • The framework shows potential for adaptation to related network optimization problems.