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A new human-inspired metaheuristic algorithm for solving optimization problems based on mimicking sewing training.

Mohammad Dehghani1, Eva Trojovská2, Tomáš Zuščák1

  • 1Department of Mathematics, Faculty of Science, University of Hradec Králové, Rokitanského 62, 500 03, Hradec Králové, Czech Republic.

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A new metaheuristic algorithm, Sewing Training-Based Optimization (STBO), inspired by sewing instruction, effectively solves complex optimization problems. STBO demonstrates superior exploration and exploitation balance compared to existing methods.

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Area of Science:

  • Computational Intelligence
  • Optimization Algorithms
  • Metaheuristics

Background:

  • Optimization problems are prevalent across scientific and engineering disciplines.
  • Existing metaheuristic algorithms often struggle with balancing exploration and exploitation.
  • Novel algorithms are needed to address complex optimization challenges effectively.

Purpose of the Study:

  • To introduce and mathematically model a novel human-based metaheuristic algorithm named Sewing Training-Based Optimization (STBO).
  • To evaluate the performance of STBO on a diverse set of benchmark functions.
  • To demonstrate the applicability of STBO to real-world engineering design problems.

Main Methods:

  • The STBO algorithm was developed, inspired by the process of teaching sewing skills.
  • The algorithm was mathematically modeled in three phases: training, imitation, and practice.
  • STBO was tested on 52 benchmark functions, including unimodal, multimodal, and the CEC 2017 test suite.
  • Performance was benchmarked against eleven established metaheuristic algorithms.

Main Results:

  • STBO exhibited strong exploration and exploitation capabilities on benchmark functions.
  • Comparative analysis showed STBO outperformed eleven other metaheuristic algorithms in solving benchmark problems.
  • STBO successfully addressed four engineering design problems, showcasing its real-world applicability.

Conclusions:

  • Sewing Training-Based Optimization (STBO) is a competitive and effective metaheuristic algorithm.
  • STBO demonstrates a superior ability to balance exploration and exploitation.
  • The algorithm shows significant potential for solving complex optimization tasks in both theoretical and practical domains.