To guide health care decision, modeling efforts have mainly focused on cost-effectiveness appraisals (CEAs) between two mutually exclusive interventions. As CEAs do not document the impact of interventions on health care budget, they are generally complemented with budget impact analysis (BIAs). BIAs provide financial projections only and do not detail the beneficial health effect an intervention may have on the population targeted. Additionally, decision makers may have different and several competing preferences and priorities on what constitutes the population health value of an intervention. A typical example is the public health impact of large childhood vaccination campaigns. Reduction of incidence, prevalence, hospitalizations, deaths, costs, etc. are the many criteria assessed by decision makers beyond the QALYs gained when they contemplate vaccination campaigns. In this research, we design a transparent dynamic budget optimization model based on a multi-criteria decision making framework. The model is a sequential multi-birth cohort model with yearly cycle and adaptable time-horizon (from 3 years onwards). Optimization is realized yearly based on the population outcomes achieved the year before, the annual budget constraints and through different combinations and weightings of decision preferences. Decision maker preferences can be weighted on number of cases avoided, GP visits avoided, hospitalizations avoided, length of in-hospital stay reduction, number of in-hospital beds avoided, number of death avoided, Life-Years gain and QALYs gain. The model is intended to address specific questions that usually emanate from decision makers confronted with the introduction of mass vaccination campaigns: What is the yearly budget needed to achieve specific public health goals? What are the yearly and overall expected outcomes at the population level (i.e. the public health impact or in others words, the return-on-investment in terms of public health benefit)? Which intervention should be given additional (less) resources to maximize (minimize) impact if the available budget is increased (decreased)?