Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Group Search Optimizer and Its Applications on Multi-objective Structural Optimal Design
Abstract There are some problems in multi-objective optimization of engineering structures, such as, the difficulties in dealing with the constraints, the complexity of program and the low computational efficiency. To solve these problems, an improved group search optimizer, named Multi-objective Group Search Optimizer (MGSO), and combined with Pareto solutions theory is presented in this chapter. Different types of examples are employed to evaluate the performance of MGSO, including truss structures and frame structures with continuous variables or discrete variables. The calculation results show the feasibility, practicality and superiority of MGSO in structure optimal design. As a stochastic algorithm, MGSO has excellent performance in terms of convergence rate. Only the best individual is needed to be selected and partial constraints are needed to be checked to find the producer, thus a great deal of computational time is saved. The MGSO is of obvious advantages for complex engineering problems especially for high-dimensional ones.
Group Search Optimizer and Its Applications on Multi-objective Structural Optimal Design
Abstract There are some problems in multi-objective optimization of engineering structures, such as, the difficulties in dealing with the constraints, the complexity of program and the low computational efficiency. To solve these problems, an improved group search optimizer, named Multi-objective Group Search Optimizer (MGSO), and combined with Pareto solutions theory is presented in this chapter. Different types of examples are employed to evaluate the performance of MGSO, including truss structures and frame structures with continuous variables or discrete variables. The calculation results show the feasibility, practicality and superiority of MGSO in structure optimal design. As a stochastic algorithm, MGSO has excellent performance in terms of convergence rate. Only the best individual is needed to be selected and partial constraints are needed to be checked to find the producer, thus a great deal of computational time is saved. The MGSO is of obvious advantages for complex engineering problems especially for high-dimensional ones.
Group Search Optimizer and Its Applications on Multi-objective Structural Optimal Design
Li, Lijuan (Autor:in) / Liu, Feng (Autor:in)
01.01.2011
40 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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