A constrained optimization evolutionary algorithm based on membrane computing

Based on membrane computing (MCCOP for short), a constrained optimization evolutionary algorithm is proposed with the evolutionary operations and strategies designed. In MCCOP, a membrane is associated with a constraint and the tentative solutions evolved according to the rules in the membrane. And it is evaluated by the constraint function value as the fitness. The subpopulations can communicate efficiently during the evolution process by making use of the structure of P systems and the communication mechanism among the membranes. The computational experiments show that MCCOP can converge to optimal or close to optimal solutions efficiently and that MCCOP outperforms or performs similarly to the other techniques referred to in terms of the quality of the resulting solutions.