KINETIC-MODEL REDUCTION USING GENETIC ALGORITHMS

Large reaction networks pose difficulties in simulation and control wh en computation time is restricted. We present a novel approach to simp lification of reaction networks that formulates the model reduction pr oblem as an optimization problem and solves it using a genetic algorit hm (GA). Two formulations of kinetic model reduction and their encodin gs are considered, one involving the elimination of reactions and the other the elimination of species. The GA approach is applied to reduce an 18-reaction, 10-species network, and the quality of solutions retu rned is evaluated by comparison with global solutions found using comp lete enumeration. The two formulations are also solved for a 32-reacti on, 18-species network. (C) 1997 Elsevier Science Ltd.