PERFORMANCE OF DIFFERENT ANT-BASED ALGORITHMS FOR OPTIMIZATION OF MIXED VARIABLE DOMAIN IN CIVIL ENGINEERING DESIGNS
- سال انتشار: 1390
- محل انتشار: مجله بهینه سازی در مهندسی عمران، دوره: 2، شماره: 1
- کد COI اختصاصی: JR_IJOCE-2-1_008
- زبان مقاله: انگلیسی
- تعداد مشاهده: 135
نویسندگان
چکیده
Ant colony optimization algorithms (ACOs) have been basically introduced to discrete variable problems and applied to different research domains in several engineering fields. Meanwhile, abundant studies have been already involved to adapt different ant models to continuous search spaces. Assessments indicate competitive performance of ACOs on discrete or continuous domains. Therefore, as potent optimization algorithms, it is encouraging to involve ant models to mixed-variable domains which simultaneously tackle discrete and continuous variables. This paper introduces four ant-based methods to solve mixed-variable problems. Each method is based upon superlative ant algorithms in discrete and/or continuous domains. Proposed methods’ performances are then tested on a set of three mathematical functions and also a water main design problem in engineering field, which are elaborately subject to linear and non-linear constraints. All proposed methods perform rather satisfactorily on considered problems and it is suggested to further extend the application of methods to other engineering studies.کلیدواژه ها
ant colony optimization; mixed-variable problems; water main designاطلاعات بیشتر در مورد COI
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