Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original firefly algorithm (FA) is used to solve the UCAV path planning problem. Furthermore, a new modified firefly algorithm (MFA) is prop...

Firefly algorithm (FA) is a powerful and efficient meta-heuristic which has shown effective performance in the recent literature when applied to solving engineering optimization problems. FA imitates flashing behavior of fireflies. generates solutions randomly assumes them as However, these algorithms may suffer from premature convergence poor global exploration used optimize complex high dimen...

The main aim of the present paper is to propose efficient multi-objective optimization algorithms (MOOAs) to tackle truss structure optimization problems. The proposed meta-heuristic algorithms are based on the firefly algorithm (FA) and bat algorithm (BA), which have been recently developed for single-objective optimization. In order to produce a well distributed Pareto front, some improvement...

Firefly algorithm is a meta-heuristic stochastic search with strong robustness and easy implementation. However, it also has some shortcomings, such as the "oscillation" phenomenon caused by too many attractions, which makes convergence speed slow or premature. In original FA, full attraction model consume lot of evaluation times, time complexity high. Therefore, this paper, novel firefly (EMDm...

The bio-inspired optimization techniques have obtained great attention in recent years due to its robustness, simplicity and efficiency to solve complex optimization problems. The firefly Optimization (FA or FFA) algorithm is an optimization method with these features. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be conside...

Nature-inspired methodologies are currently among the most powerful algorithms for optimization problems. This paper presents a recent nature-inspired algorithm named Firefly algorithm (FA) for automatically evolving a fuzzy model from numerical data. FA is a meta-heuristic inspired by the flashing behavior of fireflies. The rate and the rhythmic flash, and the amount of time form part of the s...

Reconfigurable antenna arrays are often capable of radiating multiple patterns by modifying the excitation phases of the elements. In this paper a method based on Firefly Algorithm (FA) has been proposed to obtain dual radiation pattern from a concentric ring array of isotropic elements, by finding out two different combinations of states for the switches, which are assumed to be connected with...

The recent improvements of Graphics Processing Units (GPU) have provided to the bio-inspired algorithms a powerful processing platform. Indeed, a lot of highly parallelizable problems can be significantly accelerated using GPU architecture. Among these algorithms, the Firefly Algorithm (FA) is a newly proposed method with potential application in several real world problems such as variable sel...

Scheduling jobs on computational grids is identified as NP-complete problem due to the heterogeneity of resources; the resources belong to different administrative domains and apply different management policies. This paper presents a novel metaheuristics method based on Firefly Algorithm (FA) for scheduling jobs on grid computing. The proposed method is to dynamically create an optimal schedul...

Metaheuristic algorithms have been hybridized with the standard K-means to address latter’s challenges in finding a solution automatic clustering problems. However, distance calculations required phase of hybrid increase as number clusters increases, and associated computational cost rises proportion dataset dimensionality. The use algorithm metaheuristic-based for high-dimensional real-world d...