An Asynchronous P System with Branch and Bound for Solving Hamiltonian Cycle Problem In the membrane computing, the exponential number of membranes is usually used for computationally hard problems to create exhaustive solutions. However, the number of membranes means the number of cells, and reduction of the number of membranes must be considered because the cells cannot be created exponentially. In the paper, we propose an asynchronous P system for Hamiltonian cycle using with branch and bound to reduce the number of membranes. In addition, we evaluate the number of membrane used in the known and the proposed P systems with experimental simulations. The experimental results show validity and efficiency of the proposed P system.

An Advanced Membrane Evolutionary Algorithm for Constrained Engineering Design Problems. The main goal of this paper is to propose an advanced dynamic membrane algorithm (ADMAPSOGA) based on the particle swarm optimization (PSO) and genetic algorithm (GA) for solving the constrained problems in engineering design. The proposed algorithm combines membrane computing with the particle swarm optimization and genetic algorithm. In the PSO phase, the worst solutions are enhanced by the globallocal best inertia weight and acceleration coefficients. In the second phase, crossover and mutation operators have been used to further improve the balance between the exploration and exploitation ability in PSO. The constraints are handled using a parameterfree penalty function. Several wellknown engineering design problems have been used to measure the performance of the proposed algorithm in this paper. The simulation results show that the proposed algorithm is superior to the stateoftheart algorithms.