Swarm heuristic for identifying preferred solutions in surrogate-based multi-objective engineering design

AIAA Journal

Volumn 49, Issue 7, 2011, Pages 1437-1449

  Carrese, Robert ^a,c   Sóbester, András ^b,d   Winarto, Hadi ^a,c   Li, Xiaodong ^a,e  

^a RMIT UNIVERSITY   (Australia)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^c School of Aerospace Mechanical and Manufacturing   (Australia)

^d Computational Engineering and Design ^*  (United Kingdom)

^e School of Computer Science and Information Technology   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ACCELERATED CONVERGENCE; COMPUTATIONAL BUDGET; COMPUTATIONAL BURDEN; CROSS-SECTIONAL DESIGN; DESIGN PROBLEMS; ENGINEERING DESIGN; HIGH FIDELITY; MULTI OBJECTIVE; MULTI OBJECTIVE PARTICLE SWARM OPTIMIZATION; MULTIDISCIPLINARY PROBLEMS; OBJECTIVE FUNCTIONS; OPTIMIZATION FRAMEWORK; PARETO FRONTIERS; PARTICLE SWARM; PREFERRED SOLUTIONS; SEARCH METHOD; SURROGATE MODEL; TEST PROBLEM;

DESIGN; FUSELAGES; INTERPOLATION; PARTICLE SWARM OPTIMIZATION (PSO);

MULTIOBJECTIVE OPTIMIZATION;

EID: 79959771640     PISSN: 00011452     EISSN: None     Source Type: Journal    
DOI: 10.2514/1.J050819     Document Type: Article

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