DNA sequence optimization using constrained multi-objective evolutionary algorithm

Generating a set of the good DNA sequences needs to optimize multiple objectives and to satisfy several constraints. Therefore, it can be regarded as an instance of constrained multiobjective optimization problem. We apply the controlled elitist nondominating sorting genetic algorithm with constrained tournament selection to this problem. First, multiobjective approach and constrained multiobjective approach are compared in terms of the effectiveness in finding feasible the solutions. Then the performance is evaluated by comparing with the good sequences published in literature.