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 …

In the past, the notion of fitness landscapes has found widespread adoption. Many different
methods have been developed that provide a general and abstract framework applicable to …

Stochastic local search (SLS) algorithms are among the most successful techniques for
solving computationally hard problems from computing science, operations research and …

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

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

Multi-solution problems extensively exist in practice. Particularly, the traveling salesman
problem (TSP) may possess multiple shortest tours, from which travelers can choose one …

There are three main drawbacks of current evolutionary approaches for determining the
weights of ontology matching system. The first drawback is that it is difficult to simultaneously …

TSP (traveling salesman problem) is one of the typical NP-hard problems in combinatorial
optimization problem. An improved genetic algorithm with reinforcement mutation, named …

This correspondence describes a hybrid genetic algorithm (GA) to find high-quality solutions
for the traveling salesman problem (TSP). The proposed method is based on a parallel …

Priority rules combined with schedule generation schemes are a usual approach to online
scheduling. These rules are commonly designed by experts on the problem domain …