Researchers Develop Novel Algorithm for Global Optimization and Engineering Design Problems

Strategic Insights -

Researchers at Gazi University have created a novel algorithm to overcome the limitations of existing methods in global optimization and engineering design problems. The new algorithm, called FDB-NSM-LSHADE-EpSin, combines the efficiency of fitness-distance balance (FDB) and natural survivor method (NSM) with the differential evolution (DE) algorithm, resulting in a more powerful and effective solution. This breakthrough was achieved after analyzing 54 global optimization problems, where the new algorithm outperformed its competitors in 8 out of 10 cases.

Key Takeaways:

  • The FDB-NSM-LSHADE-EpSin algorithm combines the advantages of fitness-distance balance (FDB) and natural survivor method (NSM) with the differential evolution (DE) algorithm.
  • The algorithm was tested on 54 global optimization problems, where it outperformed its competitors in 8 out of 10 cases.
  • The new algorithm was able to achieve a higher success rate than its competitor in computational complexity analyses.
  • FDB-NSM-LSHADE-EpSin ranked 1st in a comparison with 24 different competitive algorithms.
  • The algorithm was also tested on 10 different constrained real-world engineering problems, where it outperformed its competitor in 8 out of 10 cases.
  • The proposed algorithm achieved a higher success rate than its competitor in computational complexity analyses.

Statistics:

  • Average Friedman scores of FDB-NSM-LSHADE-EpSin and LSHADE-EpSin for 54 cases: 1.35 and 1.65, respectively.
  • Number of cases where FDB-NSM-LSHADE-EpSin outperformed its competitor: 8 out of 10.
  • Ranking of LSHADE-EpSin in comparison with 24 different competitive algorithms: 5th.
  • Ranking of FDB-NSM-LSHADE-EpSin in comparison with 24 different competitive algorithms: 1st.
  • Number of cases where FDB-NSM-LSHADE-EpSin achieved a higher success rate than its competitor in computational complexity analyses: 10 out of 10.

Sources:

  • A Novel Dynamic Guiding and Natural Survivor-based Evolutionary Algorithm for Global Optimisation and Engineering Design Problems: Optimum Solutions, Competitive Methods and Stability Analysis, published in The Journal of Supercomputing in 2025.
  • NewsRx LLC, October 27, 2025, "Findings from Gazi University Broaden Understanding of Mathematics (A Novel Dynamic Guiding and Natural Survivor-based Evolutionary Algorithm for Global Optimisation and Engineering Design Problems: Optimum Solutions, Competitive Methods and ...)".
  • Journal of Engineering, October 27, 2025, p 611.