As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

Several different ways exist for approaching hard optimization problems. Mathematical
programming techniques, including (integer) linear programming based methods, and …

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 …

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

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 …

In this survey we discuss different state-of-the-art approaches of combining exact algorithms
and metaheuristics to solve combinatorial optimization problems. Some of these hybrids …

The interest about hybrid optimization methods has grown for the last few years. Indeed,
more and more papers about cooperation between heuristics and exact techniques are …

Abstract The Prize-Collecting Steiner Tree Problem (PCST) on a graph with edge costs and
vertex profits asks for a subtree minimizing the sum of the total cost of all edges in the …

This paper describes a general hybrid metaheuristic for combinatorial optimization labelled
Construct, Merge, Solve & Adapt. The proposed algorithm is a specific instantiation of a …