کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
475639 699341 2016 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Adaptive differential evolution algorithm with novel mutation strategies in multiple sub-populations
ترجمه فارسی عنوان
الگوریتم تکاملی تطبیقی ​​دیفرانسیل با استراتژی های جهش جدید در چند زیر جمعیت
کلمات کلیدی
چند زیر مجموعه جمعیتی، کنترل پارامتر انعطاف پذیر، استراتژی جایگزینی، تکامل دیفرانسیل، بهینه سازی جهانی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی


• Three novel mutation strategies are run in three sub-populations respectively.
• A novel adaptive strategy is presented to tune the systemic parameters.
• A simple replacement strategy is designed to remain good solutions.

Differential evolution (DE) algorithm has been shown to be a very effective and efficient approach for solving global numerical optimization problems, which attracts a great attention of scientific researchers. Generally, most of DE algorithms only evolve one population by using certain kind of DE operators. However, as observed in nature, the working efficiency can be improved by using the concept of work specialization, in which the entire group should be divided into several sub-groups that are responsible for different tasks according to their capabilities. Inspired by this phenomenon, a novel adaptive multiple sub-populations based DE algorithm is designed in this paper, named MPADE, in which the parent population is split into three sub-populations based on the fitness values and then three novel DE strategies are respectively performed to take on the responsibility for either exploitation or exploration. Furthermore, a simple yet effective adaptive approach is designed for parameter adjustment in the three DE strategies and a replacement strategy is put forward to fully exploit the useful information from the trial vectors and target vectors, which enhance the optimization performance. In order to validate the effectiveness of MPADE, it is tested on 55 benchmark functions and 15 real world problems. When compared with other DE variants, MPADE performs better in most of benchmark problems and real-world problems. Moreover, the impacts of the MPADE components and their parameter sensitivity are also analyzed experimentally.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Operations Research - Volume 67, March 2016, Pages 155–173
نویسندگان
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