The inherent features of dynamic bioprocesses prevent the application of conventional optimization algorithms, hence making necessary the development of tailored methods and strategies. Oil the other hand, the optimization of biotechnological processes may generate significant improvements in operating conditions and policies. Fed-batch bioprocesses are specific examples where complexity and difficulty depend on the model characteristics, the operating limits (path constraints) and the production target (objective function). We propose the use of orthogonal collocation into a simultaneous optimization approach to solve these problems. Initially, the methodology is applied to a simplified model for the biosynthesis of penicillin front glucose. Then, it is applied to a cybernetic structured model for the fermentative production of polyhydroxyalkanoates (PHAs). Results show that the discretization of differential-algebraic equation (DAE) systems by orthogonal collocation in finite elements efficiently transforms dynamic optimization problems into nonlinear programming (NLP) problems, thus enabling to solve complex problems with several control variables satisfying the approximation error tolerance. (C) 2003 Elsevier B.V. All rights reserved.