Scheduling projects within owners' portfolios has largely been dealt independently from the owner's financial planning. However, financially feasible schedules could be obtained only by integrating the two aspects. Also, due to the economic fluctuations and the dynamic characteristic of the portfolios, owners usually need to reconsider the schedules of their portfolios' projects under their constrained-budget amounts. Accordingly, owners need to impose the financial constraints of their constrained-budget while scheduling for their portfolios' projects in order to align the timing and the amounts of payments with their constrained-budget amounts. This research presents a Genetic Algorithms (GA) model to optimize the schedules of multiple projects within owners' portfolios under constrained budget amounts. The model allows the owners to assign weights to rank projects based on the priority of their timely completion. Accordingly, the minimization of the total weighted projects' delays is adopted as the objective of the optimization model. In the current research, a genetic algorithms model is developed using two representation systems of activity list (AL) and random key (RK). A time-based cash flow model is adopted in which progressive payments are occurred on a monthly basis, whereas the constrained-budget amounts are allocated to the portfolios on a multi-month budgetary period basis. The developed model is successfully tested on randomly generated problems of different sizes. Accordingly, the model is expected to be capable of solving real size problems.