A new genetic algorithm methodology for design optimization of truss structures: Bipopulation-based genetic algorithm with enhanced interval search
Citation
Talaslioglu, T. (2009). A new genetic algorithm methodology for design optimization of truss structures: Bipopulation-based genetic algorithm with enhanced interval search. Modelling and Simulation in Engineering, 2009. DOI: 10.1155/2009/615162Abstract
A new genetic algorithm (GA) methodology, Bipopulation-Based Genetic Algorithm with Enhanced Interval Search (BGAwEIS), is introduced and used to optimize the design of truss structures with various complexities. The results of BGAwEIS are compared with those obtained by the sequential genetic algorithm (SGA) utilizing a single population, a multipopulation-based genetic algorithm (MPGA) proposed for this study and other existing approaches presented in literature. This study has two goals: outlining BGAwEIS's fundamentals and evaluating the performances of BGAwEIS and MPGA. Consequently, it is demonstrated that MPGA shows a better performance than SGA taking advantage of multiple populations, but BGAwEIS explores promising solution regions more efficiently than MPGA by exploiting the feasible solutions. The performance of BGAwEIS is confirmed by better quality degree of its optimal designations compared to algorithms proposed here and described in literature. Copyright (C) 2009 Tugrul Talaslioglu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.