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Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm

Research output: Contribution to journal › Article › peer-review

Standard Standard

Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm. / Seydi, Vahid; Teshnehlab, Mohamad; Aliyari Shoordeli, Mehdi.
In: Journal of Advances in Computer Engineering and Technology, Vol. 1, No. 2, 01.05.2015, p. 29-38.

Research output: Contribution to journal › Article › peer-review

HarvardHarvard

Seydi, V, Teshnehlab, M & Aliyari Shoordeli, M 2015, 'Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm', Journal of Advances in Computer Engineering and Technology, vol. 1, no. 2, pp. 29-38.

APA

Seydi, V., Teshnehlab, M., & Aliyari Shoordeli, M. (2015). Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm. Journal of Advances in Computer Engineering and Technology, 1(2), 29-38.

CBE

Seydi V, Teshnehlab M, Aliyari Shoordeli M. 2015. Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm. Journal of Advances in Computer Engineering and Technology. 1(2):29-38.

MLA

Seydi, Vahid, Mohamad Teshnehlab and Mehdi Aliyari Shoordeli. "Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm". Journal of Advances in Computer Engineering and Technology. 2015, 1(2). 29-38.

VancouverVancouver

Seydi V, Teshnehlab M, Aliyari Shoordeli M. Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm. Journal of Advances in Computer Engineering and Technology. 2015 May 1;1(2):29-38.

Author

Seydi, Vahid ; Teshnehlab, Mohamad ; Aliyari Shoordeli, Mehdi. / Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm. In: Journal of Advances in Computer Engineering and Technology. 2015 ; Vol. 1, No. 2. pp. 29-38.

RIS

TY - JOUR

T1 - Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm

AU - Seydi, Vahid

AU - Teshnehlab, Mohamad

AU - Aliyari Shoordeli, Mehdi

PY - 2015/5/1

Y1 - 2015/5/1

N2 - This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule based system is optimized using Genetic Algorithm (GA). The proposed modified CA algorithm is compared with several other optimization algorithms including GA, particle swarm optimization (PSO), especially standard version of cultural algorithm. The obtained results demonstrate that the proposed modification enhances the performance of the CA in terms of global optimality.

AB - This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule based system is optimized using Genetic Algorithm (GA). The proposed modified CA algorithm is compared with several other optimization algorithms including GA, particle swarm optimization (PSO), especially standard version of cultural algorithm. The obtained results demonstrate that the proposed modification enhances the performance of the CA in terms of global optimality.

M3 - Article

VL - 1

SP - 29

EP - 38

JO - Journal of Advances in Computer Engineering and Technology

JF - Journal of Advances in Computer Engineering and Technology

IS - 2

ER -