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Related Concept Videos

Average Power01:13

Average Power

597
In practical electrical applications, the concept of time-varying instantaneous power is not frequently utilized. Instead, focus shifts to the more practical quantity known as average power. Average power is determined by integrating the instantaneous power over a specified time period and subsequently dividing it by that duration.
597

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Running-Time Analysis of Brain Storm Optimization Based on Average Gain Model.

Guizhen Mai1, Fangqing Liu2, Yinghan Hong1

  • 1School of Physics and Electronic Engineering, Hanshan Normal University, Chaozhou 521041, China.

Biomimetics (Basel, Switzerland)
|February 23, 2024
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Summary

This study analyzes the running time of Brain Storm Optimization (BSO) variants. Results show BSO with disrupting operators and standard normal mutation are more efficient for optimization tasks.

Keywords:
average gain modelbrain storm optimization (BSO)linear functionmutation operatorrunning time

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Area of Science:

  • Evolutionary Computation
  • Algorithm Analysis
  • Optimization Techniques

Background:

  • Brain Storm Optimization (BSO) is increasingly used in industry.
  • Theoretical analysis of BSO's running time is limited.
  • Running-time analysis is crucial for evaluating algorithm efficiency.

Purpose of the Study:

  • To estimate upper bounds of expected first hitting time for six single-individual BSO variants.
  • To theoretically analyze the efficiency of different BSO configurations.
  • To provide insights into BSO's performance characteristics.

Main Methods:

  • Utilized the average gain model for theoretical analysis.
  • Estimated upper bounds of expected first hitting time.
  • Investigated six single-individual Brain Storm Optimization variants.

Main Results:

  • Time complexity for all six variants is O(n) for linear functions.
  • BSO variants with disrupting operators show faster convergence.
  • Standard normal mutation is more efficient than uniform mutation.

Conclusions:

  • Theoretical analysis provides insights into BSO variant efficiency.
  • The choice of mutation operator significantly impacts convergence speed.
  • BSO variants with disrupting operators offer improved performance.