Evolutional solutions by using PSO for 0-1 combinatorial optimization problems with constraints

In this paper, as one of global optimization methods for 0-1 combinatorial optimization problems with constraints, a continuous relaxation approach is presented, in which the continuous variables are transformed into binary variables through a sorting procedure of continuous variables taking the constraints into consideration. The new type of relaxation approach enables us to apply Particle Swarm Optimization, which is effective heuristic method for global optimization with continuous variables. Here, our presented approach is interpreted as one of evolutional computing methods because the transformation of continuous variables into binary ones corresponds to transform genotype into phenotype, which is reverse to a relation in usual evolutional computing.