We introduce the PESO+algorithm (Particle Evolutionary Swarm Optimization Plus) for the solution of single objective constrained optimization problems. A novel feature introduced by PESO+is an external archive to store and retrieve “ tolerant” particles found at past tolerance values. This technique is aimed to preserve particles that otherwise would be lost after the adjustment of the tolerance of equality constraints. Also, two perturbation operators, “ c-perturbation” and “ m-perturbation” are described. The goal of these operators is to keep diversity and to prevent premature convergence. The constraint handling technique is based on feasibility and summation of constraint violations. All experimental results are reported as required by the organizers of the special session on “ Constrained Real Parameter Optimization” at CEC2006.