Memetic Algorithms have been proven to be successful to find the nearest optimum solution to hard combinatorial optimization problems. In this paper, Memetic algorithm is designed for Asymmetric Traveling salesman problem (ATSP). Memetic Algorithm is a combination of power of Genetic algorithm with the powerful local search technique to focus on the population of local optima. Because of perfor...

This contribution presents a new memetic algorithm for continuous optimization problems, which is specially designed for applying intense local search methods. These local search methods make use of explicit strategy parameters to guide the search, and adapt these parameters with the purpose of producing more effective solutions. They may achieve accurate results, at the cost of requiring high ...

A memetic algorithm (MA), i.e. an evolutionary algorithm making use of local search, for the quadratic assignment problem is presented. A new recombination operator for realizing the approach is described, and the behavior of the MA is investigated on a set of problem instances containing between 25 and 100 facilities/locations. The results indicate that the proposed MA is able to produce high ...

The unconstrained binary quadratic programming (UBQP) problem is a general NP-hard problem with various applications. In this paper, we present a multilevel algorithm designed to approximate large UBQP instances. The proposed multilevel algorithm is composed of a backbone-based coarsening phase, an asymmetric uncoarsening phase and a memetic refinement phase, where the backbone-based procedure ...

This paper provides evolutionary approaches in order to extract comprehensible and accurate classification rules. Indeed to construct a model of classification tone must extract not only accurate rules but comprehensible also, to help the human interpretation of the model and the decision make process. In this paper the authors describe a purely genetic approach, then a tabu search approach and...

Optimal expansion of medium-voltage power networks is a common issue in electrical distribution planning. Minimizing total cost of the objective function with technical constraints and reliability limits, make it a combinatorial problem which should be solved by optimization algorithms. This paper presents a new hybrid simulated annealing and tabu search algorithm for distribution network expan...

This paper deals with the construction of binary sequences with low autocorrelation, a very hard problem with many practical applications. The paper analyzes several metaheuristic approaches to tackle this kind of sequences. More specifically, the paper provides an analysis of different local search strategies, used as standalone techniques and embedded within memetic algorithms. One of our pro...

This paper presents a genetic algorithm for an important computational biology problem. The problem appears in the computational part of a new proposal for DNA sequencing denominated sequencing by hybridization. The general usage of this method for real sequencing purposes depends mainly on the development of good algorithmic procedures for solving its computational phase. The proposed genetic ...