A Population-P-Systems-Inspired Membrane Algorithm for Multi-objective Optimization

This paper proposes a Population-P-Systems-inspired Membrane Algorithm (PPSMA) for multi-objective optimization. In the algorithm, the cells of population P systems are divided into two groups to implement different functions and the communications among cells are performed at two levels in order to obtain well converged and distributed solution set. Moreover, differential evolution is employed as search operator in PPSMA. Twelve multi-objective benchmark problems are utilized to test algorithm performance. Experimental results show that PPSMA performs better than five compared algorithms.