where An is the n-fold product of the σ-algebra A of subsets of a given set X , Fi, Gi, i∈ p ≡ {1,2, . . . , p}, and Hj , j ∈ q, are real-valued functions defined on An, and for each i∈ p, Gi(S) > 0 for all S∈An such that Hj(S) ≤ 0, j ∈ q. Optimization problems of this type in which the functions Fi, Gi, i∈ p, and Hj , j ∈ q, are defined on a subset of Rn (n-dimensional Euclidean space) are cal...

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...

Firefly algorithm is a swarm based metaheuristic algorithm inspired by the flashing behavior of fireflies. It is an effective and an easy to implement algorithm. It has been tested on different problems from different disciplines and found to be effective. Even though the algorithm is proposed for optimization problems with continuous variables, it has been modified and used for problems with n...

This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA), for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i) the mutual attraction between males and females...

Antenna array is the most important aspect to improve the communication process. The objective of this paper are to minimize the maximum side lobe level (SLL) and perform null steering for linear antenna arrays by controlling different parameters of the array elements (phase, position and amplitude). The Nature inspired optimization methods like Taguchi’s Optimization Method (TM), Self-Adaptive...