A genetic algorithm with utilizing lethal chromosomes

Many unsatisfied solutions being produced in applying GA to solve the constrained combinatorial optimization problems due to genetic operations. The unsatisfied solutions are regarded as lethal chromosomes in GA. Large numbers of lethal chromosomes might lead to that implementing and searching performance of GA comes to degrade. The usual means dealing with the lethal chromosomes is to eliminate it from population, however, evolved lethal chromosomes containing some fruits of evolution, abandoning lethal chromosomes is as same as abandoning available information, and leads to waste of evolving resources. We propose a new method to revive and utilize the lethal chromosomes based on immune theory, and apply it as a double islands algorithm model. To Multidimensional Knapsack Problem (MKP), simulating experiment shows that proposed method could effectively improve the performance of GA.