An ant system for the maximum independent set problem

Early applications of Ant Colony Optimization (ACO) have been mainly concerned with solving ordering problems (e.g., the Traveling Salesperson Problem). More recently, promising results were obtained for solving the Multiple Knapsack Problem by introducing a modification of the standard Ant System algorithm. In this paper we extend our study on the applicability of the ACO approach to subset problems. The computational study involves its applicability for solving the Maximum Independent Set Problem (MISP). The set of instances tested were either randomly generated by specific methods or taken from the so-called DIMACS benchmark graphs. The reported results which are comparable with different state-of-the-art algorithms show the potential of the ACO approach for solving the MISP.Eje: Sistemas inteligentesRed de Universidades con Carreras en Informática (RedUNCI

MCPC: another approach to crossover in genetic algorithms

Genetic algorithms (GAs) are stochastic adaptive algorithms whose search method is based on simulation of natural genetic inheritance and Darwinian strive for survival. They can be used to find approximate solutions to numerical optimization problems in cases where finding the exact optimum is prohibitively expensive, or where . no algorithm is known. The main operator, which is the driving force of genetic algorithms, IS crossover. It combines the features of two parents and produces two offspring. This paper propases a Multiple Crossover Per Couple (MCPC) approach as an altemate method for crossover operators.Eje: Diseño de algoritmosRed de Universidades con Carreras en Informática (RedUNCI

An ant system for the maximum independent set problem

Early applications of Ant Colony Optimization (ACO) have been mainly concerned with solving ordering problems (e.g., the Traveling Salesperson Problem). More recently, promising results were obtained for solving the Multiple Knapsack Problem by introducing a modification of the standard Ant System algorithm. In this paper we extend our study on the applicability of the ACO approach to subset problems. The computational study involves its applicability for solving the Maximum Independent Set Problem (MISP). The set of instances tested were either randomly generated by specific methods or taken from the so-called DIMACS benchmark graphs. The reported results which are comparable with different state-of-the-art algorithms show the potential of the ACO approach for solving the MISP.Eje: Sistemas inteligentesRed de Universidades con Carreras en Informática (RedUNCI

MCPC: another approach to crossover in genetic algorithms

Genetic algorithms (GAs) are stochastic adaptive algorithms whose search method is based on simulation of natural genetic inheritance and Darwinian strive for survival. They can be used to find approximate solutions to numerical optimization problems in cases where finding the exact optimum is prohibitively expensive, or where . no algorithm is known. The main operator, which is the driving force of genetic algorithms, IS crossover. It combines the features of two parents and produces two offspring. This paper propases a Multiple Crossover Per Couple (MCPC) approach as an altemate method for crossover operators.Eje: Diseño de algoritmosRed de Universidades con Carreras en Informática (RedUNCI