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An improved linear prediction evolution algorithm based on topological opposition-based learning for optimization.

A M Mohiuddin1, Jagdish Chand Bansal1

  • 1South Asian University, New Delhi, India.

Methodsx
|December 27, 2023
PubMed
Summary
This summary is machine-generated.

A novel topological opposition-based learning strategy enhances the improved linear prediction evolution algorithm (ILPE). This method treats population dynamics as a time series, improving optimization problem-solving effectiveness and accuracy.

Keywords:
Grey prediction evolutionary algorithmLinear prediction evolution algorithmMathematical inspired algorithmNon-linear least square fittingOpposition based learningOptimization technique

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Area of Science:

  • Computational Intelligence
  • Optimization Algorithms
  • Meta-heuristic Techniques

Background:

  • Prediction-based evolutionary algorithms are an emerging class of meta-heuristic optimization techniques.
  • The improved linear prediction evolution algorithm (ILPE) is a recent meta-heuristic inspired by non-linear least-square fitting models.

Purpose of the Study:

  • To integrate topological opposition-based learning into the ILPE framework.
  • To develop a novel reproduction operator for generating trial individuals in evolutionary algorithms.

Main Methods:

  • The proposed algorithm, Topological Improved Linear Prediction Evolution (TILPE), utilizes a non-linear least-square fitting model combined with topological opposition-based learning.
  • TILPE treats population series as time series data to predict subsequent population generations.
  • A new reproduction operator is constructed, replacing traditional mutation and crossover operators.

Main Results:

  • Numerical experiments on the CEC2014 and CEC2017 benchmark functions demonstrate the algorithm's effectiveness.
  • The proposed TILPE algorithm shows high efficacy in solving complex optimization problems.

Conclusions:

  • The integration of topological opposition-based learning significantly enhances the ILPE.
  • TILPE offers a promising approach for advancing meta-heuristic optimization techniques through time-series prediction and opposition-based learning.