کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10145946 | 1646379 | 2019 | 36 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A novel multi-objective evolutionary algorithm with fuzzy logic based adaptive selection of operators: FAME
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A novel multi-objective evolutionary algorithm with fuzzy logic based adaptive selection of operators: FAME A novel multi-objective evolutionary algorithm with fuzzy logic based adaptive selection of operators: FAME](/preview/png/10145946.png)
چکیده انگلیسی
We propose a new method for multi-objective optimization, called Fuzzy Adaptive Multi-objective Evolutionary algorithm (FAME). It makes use of a smart operator controller that dynamically chooses the most promising variation operator to apply in the different stages of the search. This choice is guided by a fuzzy logic engine, according to the contributions of the different operators in the past. FAME also includes a novel effective density estimator with polynomial complexity, called Spatial Spread Deviation (SSD). Our proposal follows a steady-state selection scheme and includes an external archive implementing SSD to identify the candidate solutions to be removed when it becomes full. To assess the performance of our proposal, we compare FAME with a number of state of the art algorithms (MOEA/D-DE, SMEA, SMPSOhv, SMS-EMOA, and BORG) on a set of difficult problems. The results show that FAME achieves the best overall performance.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 471, January 2019, Pages 233-251
Journal: Information Sciences - Volume 471, January 2019, Pages 233-251
نویسندگان
Alejandro Santiago, Bernabé Dorronsoro, Antonio J. Nebro, Juan J. Durillo, Oscar Castillo, Héctor J. Fraire,