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 …

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

Genetic algorithms (GAs) have become popular as a means of solving hard combinatorial
optimization problems. The first part of this chapter briefly traces their history, explains the …

The term 'Memetic Algorithms'[74](MAs) was introduced in the late 80s to denote a family of
metaheuristics that have as central theme the hybridization of different algorithmic …

Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms
and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical …

This paper presents a review of four decades of research on dynamic lot-sizing with capacity
constraints. We discuss both different modeling approaches to the optimization problems …

This paper presents an optimization-based solution approach for the dynamic multi-level
capacitated lot sizing problem (MLCLSP) with positive lead times. The key idea is to solve a …

This chapter reviews applications of Memetic Algorithms in the areas of business analytics
and data science. This approach originates from the need to address optimization problems …

This paper presents a new algorithm for the dynamic multi-level capacitated lot sizing
problem with setup carry-overs (MLCLSP-L). The MLCLSP-L is a big-bucket model that …

Memetic algorithms are optimization techniques based on the synergistic combination of
ideas taken from different algorithmic solvers, such as population-based search (as in …