This paper is the result of a literature study carried out by the authors. It is a review of the
different attempts made to solve the Travelling Salesman Problem with Genetic Algorithms …

Evolutionary computation has started to receive significant attention during the last decade,
although the origins can be traced back to the late 1950's. This article surveys the history as …

The deep convolutional neural network (CNN) is the state-of-the-art solution for large-scale
visual recognition. Following some basic principles such as increasing network depth and …

Faced with the challenge of solving hard optimization problems that abound in the real
world, classical methods often encounter great difficulty. Vitally important applications in …

Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for
attacking hard combinatorial optimization problems. Yet, its performance, when compared to …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …

Hybrid metaheuristics have received considerable interest these recent years in the field of
combinatorial optimization. A wide variety of hybrid approaches have been proposed in the …

A genetic algorithm is a form of evolution that occurs on a computer. Genetic algorithms are
a search method that can be used for both solving problems and modeling evolutionary …

We propose a hybrid algorithm for finding a set of nondominated solutions of a multi
objective optimization problem. In the proposed algorithm, a local search procedure is …

Ant System is a general purpose algorithm inspired by the study of the behavior of ant
colonies. It is based on a cooperative search paradigm that is applicable to the solution of …