An efficient decoder for size optimization of trusses with automatic member grouping

Toklu Y., ÖZBAŞARAN H.

Soft Computing, cilt.28, sa.19, ss.11237-11263, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28 Sayı: 19
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s00500-024-09879-6
  • Dergi Adı: Soft Computing
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, zbMATH
  • Sayfa Sayıları: ss.11237-11263
  • Anahtar Kelimeler: Colliding bodies optimization, Jaya algorithm, Member grouping, Metaheuristics, Optimization, Truss
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

This paper presents an efficient decoding method (namely SORTED decoding) for the de facto encoding in size optimization of trusses with automatic member grouping. The efficiency of the proposed method is evaluated through numerical experiments driven by two metaheuristic algorithms of different search mechanisms: Colliding Bodies Optimization and Jaya Algorithm. The first group of experiments show that the SORTED decoding method significantly outperforms the de facto and the two other decoding methods introduced in this study (ACCUMULATED and SORTED-ACCUMULATED) in terms of solution quality; moreover, the authors proved that the superiority of the SORTED decoding is not algorithm-dependent. Considerably better member-grouping configurations that provide up to 15% material economy are discovered for some of the well-known pre-grouped benchmark problems in the second group of experiments; surprisingly, the worst member-grouping configuration discovered by the SORTED decoding for one of the problems is better than that of the pre-grouped version.