ANA: Ant Nesting Algorithm for Optimizing Real-World Problems
نویسندگان
چکیده
In this paper, a novel swarm intelligent algorithm is proposed called ant nesting (ANA). The inspired by Leptothorax ants and mimics the behavior of searching for positions to deposit grains while building new nest. Although swarming ants, it does not have any algorithmic similarity with colony optimization (ACO) algorithm. It worth mentioning that ANA considered continuous updates search agent position adding rate change (e.g., step or velocity). computes differently as uses previous, current solutions, fitness values during process generate weights utilizing Pythagorean theorem. These drive agents exploration exploitation phases. benchmarked on 26 well-known test functions, results are verified comparative study genetic (GA), particle (PSO), dragonfly (DA), five modified versions PSO, whale (WOA), salp (SSA), dependent optimizer (FDO). outperformances these prominent metaheuristic algorithms several cases provides quite competitive results. Finally, employed optimizing two real-world engineering problems: antenna array design frequency-modulated synthesis. case studies demonstrate algorithm’s capability in problems.
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ژورنال
عنوان ژورنال: Mathematics
سال: 2021
ISSN: ['2227-7390']
DOI: https://doi.org/10.3390/math9233111