Two Strategies to Improve the Differential Evolution Algorithm for Optimizing Design of Truss Structures

Autor: Ching-Yun Kao, Shih-Lin Hung, Budy Setiawan
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Advances in Civil Engineering, Vol 2020 (2020)
Druh dokumentu: article
ISSN: 1687-8086
1687-8094
DOI: 10.1155/2020/8741862
Popis: The performance of differential evolution (DE) mostly depends on mutation operator. Inappropriate configurations of mutation strategies and control parameters can cause stagnation due to over exploration or premature convergence due to over exploitation. Balancing exploration and exploitation is crucial for an effective DE algorithm. This work presents an enhanced DE (EDE) for truss design that utilizes two new strategies, namely, integrated mutation and adaptive mutation factor strategies, to obtain a good balance between the exploration and exploitation of DE. Three mutation strategies (DE/rand/1, DE/best/2, and DE/rand-to-best/1) are combined in the integrated mutation strategy to increase the diversity of random search and avoid premature convergence to a local minimum. The adaptive mutation factor strategy systematically adapts the mutation factor from a large value to a small value to avoid premature convergence in the early searching period and to increase convergence to the global optimum solution in the later searching period. The outstanding performance of the proposed EDE is demonstrated through optimization of five truss structures.
Databáze: Directory of Open Access Journals
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