کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6885445 | 696520 | 2016 | 48 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A feature-driven crossover operator for multi-objective and evolutionary optimization of product line architectures
ترجمه فارسی عنوان
یک اپراتور متقاطع به منظور ویژگی چند منظوره و بهینه سازی تکاملی معماری خط تولید
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کلمات کلیدی
طراحی خط تولید محصول، الگوریتم ژنتیک چند هدفه، اپراتور متقاطع، مطالعه تجربی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
The optimization of a Product Line Architecture (PLA) design can be modeled as a multi-objective problem, influenced by many factors, such as feature modularization, extensibility and other design principles. Due to this it has been properly solved in the Search Based Software Engineering (SBSE) field. However, previous empirical studies optimized PLA design using the multi-objective and evolutionary algorithm NSGA-II, without applying one of the most important genetic operators: the crossover. To overcome this limitation, this paper presents a feature-driven crossover operator that aims at improving feature modularization in PLA design. The proposed operator was applied in two empirical studies using NSGA-II in comparison with another version of NSGA-II that uses only mutation operators. The results show the usefulness and applicability of the proposed operator. The NSGA-II version that applies the feature-driven crossover found a greater diversity of solutions (potential PLA designs), with higher feature-based cohesion, and less feature scattering and tangling.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems and Software - Volume 121, November 2016, Pages 126-143
Journal: Journal of Systems and Software - Volume 121, November 2016, Pages 126-143
نویسندگان
Thelma Elita Colanzi, Silvia Regina Vergilio,