Acronyms The full name of an acronym MOPs [1 ] Multiobjective optimization problems PSO [7 ] Particle swarm optimization MOPSOs Multiobjective particle swarm optimization algorithms MOEAs Multiobjective evolutionary algorithms GCDMOPSO Multiobjective particle swarm optimization based on cosine distance mechanism and game strategy MOPSO [9 ] Handling multiple objectives with particle swarm optimization NSGA-II [10 ] A fast and elitist multiobjective genetic algorithm PAES [11 ] Approximating the nondominated front using the Pareto archived evolution strategy SMPSO [13 ] A new PSO-based metaheuristic for multiobjective optimization MMOPSO [14 ] A novel multiobjective particle swarm optimization with multiple search strategies MOEA/D [15 ] A multiobjective evolutionary algorithm based on decomposition SDMOPSO [17 ] A novel smart multiobjective particle swarm optimization using decomposition dMOPSO [19 ] A multiobjective particle swarm optimizer based on decomposition MOPSONN [20 ] A fast multiobjective particle swarm optimization algorithm based on a new archive updating mechanism IGD [22 ] Inverted generational distance NMPSO [23 ] Particle swarm optimization with a balance able fitness estimation for many-objective optimization problems MOPSOCD [24 ] An effective use of crowding distance in multiobjective particle swarm optimization MPSO/D [18 ] A new multiobjective particle swarm optimization algorithm based on decomposition NSGA-III [25 ] An evolutionary many-objective optimization algorithm using reference point-based nondominated sorting approach, part I: solving problems with box constraints MOEAIGDNS [26 ] A multiobjective evolutionary algorithm based on an enhanced inverted generational distance metric SPEAR [27 ] A strength Pareto evolutionary algorithm based on reference direction for multiobjective and many-objective optimization SPEA2 [28 ] Improving the strength Pareto evolutionary algorithm IBEA [29 ] Indicator-based selection in multiobjective search N The population size M The number of objectives D Dimension of the decision variable FEs The maximum number of evaluations Crossover probability Mutation probability SBX Simulated binary crossover PM Polynomial-based mutation The distribution indexes of SBX The distribution indexes of PM F Parameters set by the author in differential evolution CR Parameters set by the author in differential evolution The division network number of cells Personal best particle Global best particle
