Memetic computing is a subject in computer science which considers complex structures
such as the combination of simple agents and memes, whose evolutionary interactions lead …

Evolutionary multitasking (EMT) is a newly emerging research topic in the community of
evolutionary computation, which aims to improve the convergence characteristic across …

Conventional evolutionary algorithms (EAs) are not well suited for solving expensive
optimization problems due to the fact that they often require a large number of fitness …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …

Using surrogate models in evolutionary search provides an efficient means of handling
today's complex applications plagued with increasing high-computational needs. Recent …

This paper focuses on an energy-efficient job-shop scheduling problem within a machine
speed scaling framework, where productivity is affected by deterioration. To alleviate the …

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 …

Teaching–learning based optimization (TLBO) algorithm has been recently proposed in the
literature as a novel population oriented meta-heuristic algorithm. It has been tested on …

In recent decades, a plethora of dedicated evolutionary algorithms (EAs) have been crafted
to solve domain-specific complex problems more efficiently. Many advanced EAs have …

Memetic algorithms (MAs) represent one of the recent growing areas in evolutionary
algorithm (EA) research. The term MAs is now widely used as a synergy of evolutionary or …