Biogeography-based multi-objective optimization algorithm with hybrid migration and applying in ethylene cracking process
Zheming Huang, Rongbin Qi · 2017
The Ethylene cracking is highly nonlinear, complex process with many constraints because of the complex running state of cracking furnace groups. For the solutions to multi-objective problems of yield, cost and benefits, this paper puts forward a biogeography-based multi-objective optimization algorithm with hybrid migration (BBMOHM). The hybrid migration strategy combines the self-adaptive migration with the simplex operator and the replication migration, which strengthens the convergence and the search ability, to avoid falling into local optimum. For the goal of utilizing the dominance information between individuals, this algorithm adopts the migration model of dominance degree to assist migration strategies improving the performance of the algorithm. Finally, experiments about the ZDT test function and the multi-objective optimization problem of the ethylene cracking process is verified the BBMOHM achieves good performance on convergence and distribution.