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Adaptive Bi-Operator Evolution for Multitasking Optimization Problems.

Changlong Wang1, Zijia Wang1, Zheng Kou2

  • 1School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou 510006, China.

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|October 25, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new adaptive bi-operator strategy (BOMTEA) for evolutionary multitasking optimization (EMTO). BOMTEA improves performance by adaptively selecting the best evolutionary search operator for different tasks.

Keywords:
evolutionary computation (EC)evolutionary multitask optimization (EMTO)evolutionary search operatorknowledge transfer

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Optimization Algorithms

Background:

  • Evolutionary multitasking optimization (EMTO) aims to solve multiple complex problems simultaneously using evolutionary algorithms.
  • Current EMTO algorithms often use a single evolutionary search operator (ESO), limiting adaptability and performance across diverse tasks.

Purpose of the Study:

  • To address the limitations of single-operator EMTO algorithms.
  • To propose a novel adaptive bi-operator strategy for enhanced multitasking optimization.

Main Methods:

  • Developed the multitasking evolutionary algorithms via an adaptive bi-operator strategy (BOMTEA).
  • Implemented an adaptive mechanism to control the selection probability of each ESO based on its performance.
  • Evaluated BOMTEA on CEC17 and CEC22 benchmark datasets.

Main Results:

  • BOMTEA demonstrated superior performance on benchmark multitasking problems.
  • The adaptive bi-operator strategy effectively determined the most suitable ESO for various tasks.
  • BOMTEA significantly outperformed existing comparative algorithms in multitasking optimization.

Conclusions:

  • The adaptive bi-operator strategy enhances the performance of evolutionary multitasking optimization.
  • BOMTEA offers a more flexible and effective approach to solving complex, multi-task problems.
  • This strategy represents a significant advancement in the field of EMTO.