Advanced Oxidation Processes (AOP) have been proposed as alternative water treatments coping with recalcitrant organic pollutants [1]. AOPs are based on in-situ generation of highly oxidant hydroxyl radicals. Particularly, in the photo-Fenton process they are produced from ferrous salts (Fe) and hydrogen peroxide (HP). However, this process has been acknowledged to suffer inefficient reactions scavenging HP; which has motivated a large amount of research aimed to determine efficient ratios for the initial concentrations of reactants (Fe/HP). Dosage is also reported to reduce these side reactions and improve the performance of these processes. Certainly, since they are operated batchwise, the most efficient ratio Fe/HP should not be regarded as an initial value, but as a profile that may undergo optimization. Yet, such optimization problem has not been attempted. A large experimental effort has produced empirical models that cannot be scaled up and do not address the process dynamics, while some first-principle kinetic models that can be found on the literature [2] require a high computational cost for too simple reactions. Therefore, a first issue towards optimization is model selection. This work adopts the kinetic model by Cabrera Reina [3] based on aggregated components. This model focuses on practical observable variables such as dissolved oxygen and total organic carbon (TOC), and provides a simplified modelling of delayed response of TOC and scavenging reactions. Hence, this work expands it to semi-batch operation and addresses simulation and subsequent optimization of the dosage profile using the Python and Modelica open-source programing languages. Python is used as the core providing functions that Modelica lacks, while the model is implemented in Modelica to take advantage of its model-based language. The optimization of the HP dosage profile addressed two different scenarios and objective functions. Thus, Pareto frontiers were determined to analyse trade-offs and opportunities, and to aid decision making: i) The TOC reduction to be achieved under time and HP limitations, and ii) The total HP required to attain a given conversion (TOC) within a given time horizon. Continuous and piecewise optimization approaches were tested and discussed. Results validate the importance of determining efficient dosage profiles for the photo-Fenton process. Model based optimization allows exploring opportunities and trade-offs, and aids decision-making. Hence, this study fosters further work on model fitting for specific applications.