Evolutionary algorithms are an important emergent computing methodology. They have
aroused intense interest in the past few years because of their versatility in solving difficult …

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 …

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 …

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

High competition in today's global market has forced the organisations to invest in and focus
on their logistics system. Logistics is a business planning framework for the management of …

Memetic algorithms (MAs) are optimization techniques based on the orchestrated interplay
between global and local search components and have the exploitation of specific problem …

A framework for hybridizing evolutionary algorithms with the branch-and-bound algorithm
(B&B) is presented in this paper. This framework is based on using B&B as an operator …

Reliable communication network design (RCND) is a well-known optimisation problem to
produce a network with maximum reliability. This paper addresses the minimum cost …

In this paper an evaluation of the current situation regarding Evolutionary Algorithms (EA) in
management applications is given. While assembling as many references as possible, the …