Firefly Algorithm for optimization problems with non-continuous variables: A Review and Analysis

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 non-continuous variables, including binary and integer valued problems. In this paper a detailed review of this modifications of firefly algorithm for problems with non-continuous variables will be discussed. The strength and weakness of the modifications along with possible future works will be presented.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/11/2017

Porcellio scaber algorithm (PSA) for solving constrained optimization problems

In this paper, we extend a bio-inspired algorithm called the porcellio s...
research
11/11/2020

A Review of the Family of Artificial Fish Swarm Algorithms: Recent Advances and Applications

The Artificial Fish Swarm Algorithm (AFSA) is inspired by the ecological...
research
01/27/2022

Current Studies and Applications of Shuffled Frog Leaping Algorithm: A Review

Shuffled Frog Leaping Algorithm (SFLA) is one of the most widespread alg...
research
03/12/2020

Improved Binary Artificial Bee Colony Algorithm

The Artificial Bee Colony (ABC) algorithm is an evolutionary optimizatio...
research
05/11/2015

Relations between MDDs and Tuples and Dynamic Modifications of MDDs based constraints

We study the relations between Multi-valued Decision Diagrams (MDD) and ...
research
04/25/2023

When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems

The domain of an optimization problem is seen as one of its most importa...
research
09/03/2019

Contractility of continuous optimization

By introducing the concept of contractility, all the possible continuous...

Please sign up or login with your details

Forgot password? Click here to reset