MCPC: another approach to crossover in genetic algorithms
Susana Cecilia Esquivel, Raúl Héctor Gallard, Zbigniew Michalewicz · El Servicio de Difusión de la Creación Intelectual (National University of La Plata) · 1995
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.