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Hybrid Nature-Inspired Optimization for the Cell Formation Problem with Machine Reliability and Alternative Routings.

Paulo Figueroa-Torrez1, Broderick Crawford2, Orlando Durán3

  • 1Departamento de Ciencias Industriales, Medio Ambiente y Energía, Universidad Católica Boliviana "San Pablo", Colón 734, Tarija, Bolivia.

Biomimetics (Basel, Switzerland)
|June 25, 2026
PubMed
Summary

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This summary is machine-generated.

This study compares Black Widow Optimizer and Golden Eagle Optimizer for the complex Generalized Cell Formation Problem. A hybrid approach combining Golden Eagle Optimizer with Black Widow Optimizer

Area of Science:

  • Operations Research
  • Manufacturing Systems Engineering
  • Computational Intelligence

Background:

  • The Cell Formation Problem (CFP) is crucial for cellular manufacturing efficiency, flexibility, and reliability.
  • Real-world complexities like alternative process routes and machine reliability lead to the NP-Hard Generalized Cell Formation Problem (GCFP) with machine reliability.
  • Addressing the computational complexity of GCFP requires advanced optimization techniques.

Purpose of the Study:

  • To comparatively evaluate the Black Widow Optimizer (BWO) and Golden Eagle Optimizer (GEO) for the GCFP with machine reliability.
  • To investigate the potential of hybridizing metaheuristics by integrating BWO mechanisms into GEO to improve search behavior.
  • To assess the performance and computational complexity of individual and hybrid algorithms.
Keywords:
alternative routingblack widow optimizercell formation problemgolden eagle optimizermachine reliabilitymetaheuristics hybridization

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Main Methods:

  • Comparative analysis of BWO and GEO algorithms on the GCFP with machine reliability.
  • Development and evaluation of a hybrid metaheuristic strategy combining BWO's mutation mechanism with GEO's search strategies.
  • Application of the Wilcoxon-Mann-Whitney statistical test to validate performance differences.
  • Calculation of Big-O computational complexity for algorithm assessment.

Main Results:

  • The Black Widow Optimizer (BWO) demonstrated superior individual performance compared to the Golden Eagle Optimizer (GEO), with average relative percentage deviation (RPD) values of 0.855% and 1.068%, respectively.
  • The hybrid strategy, integrating BWO's mutation mechanism into GEO, achieved the best performance with an RPD of 0.592%.
  • Statistical validation confirmed significant performance differences among the evaluated algorithms.

Conclusions:

  • Hybrid metaheuristics show significant potential for solving the Generalized Cell Formation Problem with machine reliability.
  • Integrating specific mechanisms, like mutation from BWO into GEO, can enhance optimization performance in complex manufacturing problems.
  • The findings contribute to developing more robust and efficient manufacturing systems through advanced computational approaches.