In　order　to　achieve　optimal　control　on　mechanism　model　of　fermentation　process,　We　studied　the　global　stochastic　methods　(simulated　annealing　algorithm　SA)　and　local　deterministic　method　(sequential　quadratic　programming　SQP),　Taking　into　account　the　full　use　of　their　complementary　strengths:　some　global　convergence　properties,　in　the　case　of　the　stochastic　strategy,　and　fast　convergence　if　started　close　to　the　global　solution,　in　the　case　of　the　deterministic　approach.　The　paper　proposes　a　novel　Hybrid　algorithm　which　combines　the　global　stochastic　method　(SA)　and　the　local　deterministic　method　(SQP).　In　the　hybrid　algorithm　simulated　annealing　method　is　introduced　in　the　SQP　algorithm　to　generate　new　solutions　out　of　local　minima,　and　improves　the　SA　sampling　criteria.　The　test　results　of　several　classical　COPs　using　the　hybrid　algorithm　proved　the　effectiveness　of　the　hybrid　algorithm　for　constrained　optimization　problems.　©　2011　IEEE.