In their original versions, nature-inspired search algorithms such as evolutionary algorithms
and those based on swarm intelligence, lack a mechanism to deal with the constraints of a …

Memetic computation is a paradigm that uses the notion of meme (s) as units of information
encoded in computational representations for the purpose of problem-solving. It covers a …

Differential evolution (DE) is a class of simple yet powerful evolutionary algorithms for global
numerical optimization. Binomial crossover and exponential crossover are two commonly …

Many different algorithms have been developed in the last few decades for solving complex
real-world search and optimization problems. The main focus in this research has been on …

Taking a lead from the multi-faceted definitions and roles of the term" meme" in memetics, a
plethora of potentially rich memetic computing methodologies, frameworks and operational …

Motivated by the recent success of diverse approaches based on differential evolution (DE)
to solve constrained numerical optimization problems, in this paper, the performance of this …

From the word" mimeme" of Greek origin, Dawkins coined the term" meme" in his 1976 book
on" The Selfish Gene"[1]. He defined it as being" the basic unit of cultural transmission or …

Multiobjective evolutionary algorithm based on decomposition (MOEA/D) and an improved
non-dominating sorting multiobjective genetic algorithm (NSGA-II) is two well known …

In computational intelligence, the term 'memetic algorithm'has come to be associated with
the algorithmic pairing of a global search method with a local search method. In a …

This paper reviews some state-of-the-art hybrid multiobjective evolutionary algorithms
(MOEAs) dealing with multiobjective optimization problem (MOP). The mathematical …