model of palsson and coworkers edwards and palsson 2000 the complexity and built in redundancy of this network e g the e coli model encompasses 720 reactions necessitates a systematic and efficient search approach to combat the combinatorial explosion of candidate gene knockout strategies the nested optimization framework shown in fig1 is developed to identify multiple gene deletion combinations that maximally couple cellular growth objectives with externally imposed chemical production targets this multi layered optimization structure involving two competing optimal strategists i e cellular objective and chemical production is referred to as a bilevel optimization problem bard 1998 problem formulation specifics along with an elegant solution procedure drawing upon linear programming lp duality theory are described in the methods section the optknock procedure is applied to succinate lactate and 1 3 propanediol pdo production in e coli with the maximization of the biomass yield for a fixed amount of uptaken glucose employed as the cellular objective the obtained results are also contrasted against using the minimization of metabolic adjustment moma segre et al 2002 as the cellular objective based on the optknock framework it is possible identify the most promising gene knockout strategies and their corresponding allowable envelopes of chemical versus biomass production in the context of succinate lactate and pdo.