A novel two-phase hybrid selection mechanism feeder to improve performance of many-objective optimization algorithms

[1] Deb K(2002)A fast and elitist multiobjective genetic algorithm: Nsga-ii IEEE Trans Evolut Comput 6 182-197

[2] Pratap A(2020)Solving the multi-objective flexible job shop scheduling problem with a novel parallel branch and bound algorithm Swarm Evolut Comput 53 100632-85

[3] Agarwal S(2020)A multi-objective adaptive evolutionary algorithm to extract communities in networks Swarm Evolut Comput 52 100629-4795

[4] Meyarivan T(2020)Binary differential evolution with self-learning for multi-objective feature selection Inf Sci 507 67-248

[5] Soto C(2017)Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering J Supercomput 73 4773-76

[6] Li Q(2020)An enhanced multi-objective grey wolf optimizer for service composition in cloud manufacturing Appl Soft Comput 87 106003-744

[7] Cao Z(1994)Multiobjective optimization using nondominated sorting in genetic algorithms Evolut Comput 2 221-784

[8] Ding W(2018)A competitive mechanism based multi-objective particle swarm optimizer with fast convergence Inf Sci 427 63-42

[9] Li Q(2015)A novel multi-objective particle swarm optimization with multiple search strategies Eur J Op Res 247 732-187

[10] Zhang Y(2007)On the evolutionary optimization of many conflicting objectives IEEE Trans Evolut Comput 11 770-1287

[1] Deb K(2002)A fast and elitist multiobjective genetic algorithm: Nsga-ii IEEE Trans Evolut Comput 6 182-197

[2] Pratap A(2020)Solving the multi-objective flexible job shop scheduling problem with a novel parallel branch and bound algorithm Swarm Evolut Comput 53 100632-85

[3] Agarwal S(2020)A multi-objective adaptive evolutionary algorithm to extract communities in networks Swarm Evolut Comput 52 100629-4795

[4] Meyarivan T(2020)Binary differential evolution with self-learning for multi-objective feature selection Inf Sci 507 67-248

[5] Soto C(2017)Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering J Supercomput 73 4773-76

[6] Li Q(2020)An enhanced multi-objective grey wolf optimizer for service composition in cloud manufacturing Appl Soft Comput 87 106003-744

[7] Cao Z(1994)Multiobjective optimization using nondominated sorting in genetic algorithms Evolut Comput 2 221-784

[8] Ding W(2018)A competitive mechanism based multi-objective particle swarm optimizer with fast convergence Inf Sci 427 63-42

[9] Li Q(2015)A novel multi-objective particle swarm optimization with multiple search strategies Eur J Op Res 247 732-187

[10] Zhang Y(2007)On the evolutionary optimization of many conflicting objectives IEEE Trans Evolut Comput 11 770-1287