Solution of structural and mathematical optimization problems using a new hybrid swarm intelligence optimization algorithm

Mortazavi A., TOĞAN V., Moloodpoor M.

ADVANCES IN ENGINEERING SOFTWARE, cilt.127, ss.106-123, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 127
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1016/j.advengsoft.2018.11.004
  • Dergi Adı: ADVANCES IN ENGINEERING SOFTWARE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.106-123
  • Anahtar Kelimeler: Integrated particle swarm optimization (iPSO), Teaching and learning based optimization (TLBO), Hybrid optimization method, COLLIDING BODIES OPTIMIZATION, LEARNING-BASED OPTIMIZATION, PARTICLE SWARM, TRUSS STRUCTURES, DESIGN OPTIMIZATION, TOPOLOGY OPTIMIZATION, SIZING OPTIMIZATION, SIZE, STRATEGY
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

In this investigation a new optimization algorithm named as interactive search algorithm (ISA) is presented. This method is developed through modifying and hybridizing the affirmative features of recently developed integrated particle swarm optimization (iPSO) algorithm with the pairwise knowledge sharing mechanism of the teaching and learning based optimization (TLBO) method. Proposed ISA provides two different navigation schemes as Tracking and Interacting. Each agent based on its tendency factor can pick one of these two schemes for searching the domain. Additionally, ISA utilizes an improved fly-back technique to handle problem constraints. The proposed method is tested on a set of mathematical and structural optimization benchmark problems with discrete and continuous variables. Numerical results indicate that the new algorithm is competitive with other well-stablished metaheuristic algorithms.