Enhanced Moth-flame optimizer with mutation strategy for global optimization
Y Xu, H Chen, J Luo, Q Zhang, S Jiao, X Zhang - Information Sciences, 2019 - Elsevier
Moth-flame optimization (MFO) is a widely used nature-inspired algorithm characterized by a
simple structure with simple parameters. However, for some complex optimization tasks …
simple structure with simple parameters. However, for some complex optimization tasks …
An efficient chaotic mutative moth-flame-inspired optimizer for global optimization tasks
Y Xu, H Chen, AA Heidari, J Luo, Q Zhang… - Expert Systems with …, 2019 - Elsevier
Moth-flame optimization algorithm (MFO) is a new nature-inspired meta-heuristic based on
the navigation routine of moths in the environment known as transverse orientation. For …
the navigation routine of moths in the environment known as transverse orientation. For …
MFO-SFR: An enhanced moth-flame optimization algorithm using an effective stagnation finding and replacing strategy
Moth-flame optimization (MFO) is a prominent problem solver with a simple structure that is
widely used to solve different optimization problems. However, MFO and its variants …
widely used to solve different optimization problems. However, MFO and its variants …
A double evolutionary learning moth-flame optimization for real-parameter global optimization problems
The original moth-flame optimization (MFO) algorithm neither generates high-performance
flames nor utilizes the flames to offer enough effective search guidance for moths in solution …
flames nor utilizes the flames to offer enough effective search guidance for moths in solution …
Death mechanism-based moth–flame optimization with improved flame generation mechanism for global optimization tasks
Z Li, J Zeng, Y Chen, G Ma, G Liu - Expert Systems with Applications, 2021 - Elsevier
Abstract Moth–Flame Optimization (MFO) algorithm is widely used to solve real parameter
global optimization problems. However, the original MFO algorithm has some problems …
global optimization problems. However, the original MFO algorithm has some problems …
Double adaptive weights for stabilization of moth flame optimizer: Balance analysis, engineering cases, and medical diagnosis
Moth flame optimization (MFO) is a swarm-based algorithm with mediocre performance and
marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode …
marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode …
A covariance-based Moth–flame optimization algorithm with Cauchy mutation for solving numerical optimization problems
X Zhao, Y Fang, L Liu, M Xu, Q Li - Applied Soft Computing, 2022 - Elsevier
Abstract Moth–Flame Optimization (MFO) algorithm, which is inspired by the navigation
method of moths, is a nature-inspired optimization algorithm. The MFO is easy to implement …
method of moths, is a nature-inspired optimization algorithm. The MFO is easy to implement …
Opposition-based moth flame optimization with Cauchy mutation and evolutionary boundary constraint handling for global optimization
Moth flame optimization (MFO) algorithm proves to be an excellent choice for numerical
optimization. However, for some complex objectives, MFO may get trapped in local optima or …
optimization. However, for some complex objectives, MFO may get trapped in local optima or …
An improved moth-flame optimization algorithm with adaptation mechanism to solve numerical and mechanical engineering problems
Moth-flame optimization (MFO) algorithm inspired by the transverse orientation of moths
toward the light source is an effective approach to solve global optimization problems …
toward the light source is an effective approach to solve global optimization problems …
Multi-swarm improved moth–flame optimization algorithm with chaotic grouping and Gaussian mutation for solving engineering optimization problems
X Zhao, Y Fang, S Ma, Z Liu - Expert Systems with Applications, 2022 - Elsevier
Abstract Moth–Flame Optimization (MFO) is widely utilized to solve optimization problems in
different fields since it has a simple structure and easy implementation. However, MFO …
different fields since it has a simple structure and easy implementation. However, MFO …
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