Matches in SemOpenAlex for { <https://semopenalex.org/work/W4309214447> ?p ?o ?g. }
- W4309214447 endingPage "1976" @default.
- W4309214447 startingPage "1976" @default.
- W4309214447 abstract "This paper proposes the use of enhanced comprehensive learning particle swarm optimization (ECLPSO), combined with a Gaussian local search (GLS) technique, for the simultaneous optimal size and shape design of truss structures under applied forces and design constraints. The ECLPSO approach presents two novel enhancing techniques, namely perturbation-based exploitation and adaptive learning probability, in addition to its distinctive diversity of particles. This prevents the premature convergence of local optimal solutions. In essence, the perturbation enables the robust exploitation in the updating velocity of particles, whilst the learning probabilities are dynamically adjusted by ranking information on the personal best particles. Based on the results given by ECLPSO, the GLS technique takes data from the global best particle and personal best particles in the last iteration to generate samples from a Gaussian distribution to improve convergence precision. A combination of these techniques results in the fast convergence and likelihood to obtain the optimal solution. Applications of the combined GLS-ECLPSO method are illustrated through several successfully solved truss examples in two- and three-dimensional spaces. The robustness and accuracy of the proposed scheme are illustrated through comparisons with available benchmarks processed by other meta-heuristic algorithms. All examples show simultaneous optimal size and shape distributions of truss structures complying with limit state design specifications." @default.
- W4309214447 created "2022-11-24" @default.
- W4309214447 creator A5008759629 @default.
- W4309214447 creator A5022449898 @default.
- W4309214447 creator A5055150917 @default.
- W4309214447 creator A5076259271 @default.
- W4309214447 date "2022-11-14" @default.
- W4309214447 modified "2023-09-26" @default.
- W4309214447 title "Combined Gaussian Local Search and Enhanced Comprehensive Learning PSO Algorithm for Size and Shape Optimization of Truss Structures" @default.
- W4309214447 cites W1519405745 @default.
- W4309214447 cites W1983137691 @default.
- W4309214447 cites W1988435419 @default.
- W4309214447 cites W1997986228 @default.
- W4309214447 cites W1998519521 @default.
- W4309214447 cites W2005595061 @default.
- W4309214447 cites W2006061810 @default.
- W4309214447 cites W2011464354 @default.
- W4309214447 cites W2013446578 @default.
- W4309214447 cites W2014202058 @default.
- W4309214447 cites W2022388878 @default.
- W4309214447 cites W2032177983 @default.
- W4309214447 cites W2051116156 @default.
- W4309214447 cites W2052474919 @default.
- W4309214447 cites W2058350390 @default.
- W4309214447 cites W2090398263 @default.
- W4309214447 cites W2092258872 @default.
- W4309214447 cites W2131613989 @default.
- W4309214447 cites W2148980653 @default.
- W4309214447 cites W2151554678 @default.
- W4309214447 cites W219782404 @default.
- W4309214447 cites W2464587182 @default.
- W4309214447 cites W2783827472 @default.
- W4309214447 cites W2809147664 @default.
- W4309214447 cites W2810255841 @default.
- W4309214447 cites W3009979760 @default.
- W4309214447 cites W3111309620 @default.
- W4309214447 cites W3128518856 @default.
- W4309214447 cites W3182276857 @default.
- W4309214447 cites W4205656153 @default.
- W4309214447 cites W4214521484 @default.
- W4309214447 cites W4280578440 @default.
- W4309214447 doi "https://doi.org/10.3390/buildings12111976" @default.
- W4309214447 hasPublicationYear "2022" @default.
- W4309214447 type Work @default.
- W4309214447 citedByCount "3" @default.
- W4309214447 countsByYear W43092144472023 @default.
- W4309214447 crossrefType "journal-article" @default.
- W4309214447 hasAuthorship W4309214447A5008759629 @default.
- W4309214447 hasAuthorship W4309214447A5022449898 @default.
- W4309214447 hasAuthorship W4309214447A5055150917 @default.
- W4309214447 hasAuthorship W4309214447A5076259271 @default.
- W4309214447 hasBestOaLocation W43092144471 @default.
- W4309214447 hasConcept C104317684 @default.
- W4309214447 hasConcept C11413529 @default.
- W4309214447 hasConcept C119857082 @default.
- W4309214447 hasConcept C121332964 @default.
- W4309214447 hasConcept C126255220 @default.
- W4309214447 hasConcept C127413603 @default.
- W4309214447 hasConcept C141934464 @default.
- W4309214447 hasConcept C162324750 @default.
- W4309214447 hasConcept C163716315 @default.
- W4309214447 hasConcept C173534245 @default.
- W4309214447 hasConcept C173801870 @default.
- W4309214447 hasConcept C185592680 @default.
- W4309214447 hasConcept C186394612 @default.
- W4309214447 hasConcept C2777303404 @default.
- W4309214447 hasConcept C33923547 @default.
- W4309214447 hasConcept C41008148 @default.
- W4309214447 hasConcept C50522688 @default.
- W4309214447 hasConcept C55493867 @default.
- W4309214447 hasConcept C62520636 @default.
- W4309214447 hasConcept C63479239 @default.
- W4309214447 hasConcept C66938386 @default.
- W4309214447 hasConcept C85617194 @default.
- W4309214447 hasConceptScore W4309214447C104317684 @default.
- W4309214447 hasConceptScore W4309214447C11413529 @default.
- W4309214447 hasConceptScore W4309214447C119857082 @default.
- W4309214447 hasConceptScore W4309214447C121332964 @default.
- W4309214447 hasConceptScore W4309214447C126255220 @default.
- W4309214447 hasConceptScore W4309214447C127413603 @default.
- W4309214447 hasConceptScore W4309214447C141934464 @default.
- W4309214447 hasConceptScore W4309214447C162324750 @default.
- W4309214447 hasConceptScore W4309214447C163716315 @default.
- W4309214447 hasConceptScore W4309214447C173534245 @default.
- W4309214447 hasConceptScore W4309214447C173801870 @default.
- W4309214447 hasConceptScore W4309214447C185592680 @default.
- W4309214447 hasConceptScore W4309214447C186394612 @default.
- W4309214447 hasConceptScore W4309214447C2777303404 @default.
- W4309214447 hasConceptScore W4309214447C33923547 @default.
- W4309214447 hasConceptScore W4309214447C41008148 @default.
- W4309214447 hasConceptScore W4309214447C50522688 @default.
- W4309214447 hasConceptScore W4309214447C55493867 @default.
- W4309214447 hasConceptScore W4309214447C62520636 @default.
- W4309214447 hasConceptScore W4309214447C63479239 @default.
- W4309214447 hasConceptScore W4309214447C66938386 @default.
- W4309214447 hasConceptScore W4309214447C85617194 @default.
- W4309214447 hasIssue "11" @default.
- W4309214447 hasLocation W43092144471 @default.