1403/01/10
احسان جهانی

احسان جهانی

مرتبه علمی: دانشیار
ارکید:
تحصیلات: دکترای تخصصی
اسکاپوس:
دانشکده: دانشکده مهندسی و فناوری
نشانی:
تلفن: 09358549107

مشخصات پژوهش

عنوان
Tackling global optimization problems with a novel algorithm –Mouth Brooding Fish algorithm
نوع پژوهش
JournalPaper
کلیدواژه‌ها
Mouth Brooding Fish algorithm; Nature-inspired algorithm Evolutionary algorithm; Optimization algorithm
سال
2018
مجله APPLIED SOFT COMPUTING
شناسه DOI
پژوهشگران Ehsan Jahani ، Mohammad Chizari

چکیده

Nowadays, due to the fact that difficulty of global optimization problems in different fields is increasing,various methods have been introduced to solve such problems. This paper proposes a novel global opti-mization algorithm inspired by Mouth Brooding Fish in nature. Meta-heuristics based on evolutionarycomputation and swarm intelligence are outstanding examples of nature-inspired solution techniques.Mouth Brooding Fish (MBF) algorithm simulates the symbiotic interaction strategies adopted by organ-isms to survive and propagate in the ecosystem. The proposed algorithm uses the movement, dispersionand protection behavior of Mouth Brooding Fish as a pattern to find the best possible answer. Thisalgorithm is evaluated by CEC2013&14 benchmark functions for single objective optimization and theproposed algorithm competes with the advanced algorithms (CMA-ES, JADE, SaDE, and GL-25). The resultsdemonstrate that the proposed algorithm is able to construct very promising results and has merits insolving challenging optimization problems.