Firefly algorithm (FA) is a recently proposed swarm intelligence optimization technique, which has shown good performance on many optimization problems. In the standard FA and its most variants, a firefly moves to other brighter fireflies. If the current firefly is brighter than another one, the current one will not be conducted any search. In this paper, we propose a new firefly algorithm (cal...

in this research, an integrated inventory problem is formulated for a single-vendor multiple-retailer supply chain that works according to the vendor managed inventory policy. the model is derived based on the economic order quantity in which shortages with penalty costs at the retailers` level is permitted. as predicting customer demand is the most important problem in inventory systems and th...

Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications. We will compare the proposed firefly algorithm with other metaheuristic algorithms such as particle swarm optimization (PSO). Simulations and results indicate that the proposed firefly a...

Firefly algorithm is one of the new metaheuristic algorithms for optimization problems. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be considered as fireflies, and brightness is assigned depending on their performance on the objective function. One of the rules used to construct the algorithm is, a firefly will be attracte...

—Many real world problems are mostly time varying optimization problems, which require special mechanisms to detect changes in environment and then response to them. In this paper, combination of learning automata and firefly algorithm in order to improve the performance of firefly algorithm in dynamic environments has been proposed. In the algorithm, the firefly algorithm has been equipped wit...

Firefly Algorithm (FA) is one of the recent swarm intelligence methods developed by Xin-She Yang in 2008 [12]. FA is a stochastic, nature-inspired, metaheuristic algorithm that can be applied for solving the hardest optimization problems. The main goal of this paper is to analyze the influence of changing some parameters of the FA when solving bound constrained optimization problems. One of the...

This work presents a study of a new binary coded firefly algorithm. The firefly algorithm is a novel nature-inspired metaheuristic, inspired by the social behavior of fireflies, which is being applied to solve many optimization problems. We test the proposed binary coded firefly algorithm solving the non-unicost set covering problem which is a well-known NP-hard discrete optimization problem wi...

Feed-forward neural networks are popular classification tools which are broadly used for early detection and diagnosis of breast cancer. In recent years, a great attention has been paid to bio-inspired optimization techniques due to its robustness, simplicity and efficiency in solving complex optimization problems. In this paper, it is intended to introduce a Genetic Algorithm based Firefly Alg...