What is self adaptive differential evolution?

What is self adaptive differential evolution?

Abstract. A differential evolution (DE) algorithm with self-adaptive population resizing mechanism, SapsDE, is proposed to enhance the performance of DE by dynamically choosing one of two mutation strategies and tuning control parameters in a self-adaptive manner.

What is the use of differential evolution algorithm?

Differential evolution (DE) is a population based evolutionary algorithm widely used for solving multidimensional global optimization problems over continuous spaces, and has been successfully used to solve several kinds of problems.

Is differential evolution a genetic algorithm?

Conclusion. Differential Evolution differs from standard genetic algorithms in that it utilizes directional information within the population through the usage of a target and unit vector. These capabilities allow differential evolution to converge faster to solutions at the cost of poor exploration.

What is mutation in differential evolution?

DE is an evolutionary algorithm that processes a population of individuals represented by -dimensional vectors of real numbers. In each iteration, for each parent , a mutant is created by means of a differential mutation operator. The mutant is then crossed-over with the parent and yields an offspring .

What is crossover in differential evolution?

In Differential Evolution Algorithms the crossover operator allows the construction of a new trial element starting from the current and mutant elements. Thus it controls which and how many components are mutated in each element of the current population.

What is bat optimization algorithm?

A bat algorithm (BA) is a heuristic algorithm that operates by imitating the echolocation behavior of bats to perform global optimization. The BA is widely used in various optimization problems because of its excellent performance.

What are the parameters of Firefly algorithm?

Within this procedure, firefly algorithm is executed by three parameters which are attractiveness, randomization, and absorption. Attractiveness parameter is based on light intensity between two fireflies and defined with exponential functions.

What is the use of BAT algorithm?

The bat algorithm uses some idolized rules for simplicity. (1)Bats use echolocation to sense prey, predator, or any barriers in the path and distance. (2)Bats fly with a velocity and position . They have frequency f and loudness to reach their prey.

What is Firefly algorithm used for?

The firefly algorithm, in particular, is applied for solving continuous and discrete optimization problems. In order to tackle different optimization problems efficiently and fast, many variants of the firefly algorithm have recently been developed.

What is shuffled frog leaping algorithm?

Shuffled Frog Leaping Algorithm (SFLA) is one of the most widespread algorithms. It was developed by Eusuff and Lansey in 2006. SFLA is a population-based metaheuristic algorithm that combines the benefits of memetics with particle swarm optimization.