Project Portfolio Selection
IntroductionProject portfolio selection plays a significant role in many organizations. The project is a unique set of coordinated activities with a clear starting and ending point where a specific goal is achieved by individuals or organizations within a specific timeframe, cost and performance parameters. Selecting is not only about selecting out the right project but also ensuring the achievement of the corporate strategy within the limit of company’s resources and capabilities. Selecting the optimal projects from a large number of projects with various constraints and interdependences can be very challenging. Different tools had been developed for project portfolio selection problem, such as goal programming, binary integer linear programming and decision trees, etc. Each tool has its own advantages and disadvantages. Therefore, selecting an appropriate tool is also critical in the project management. In this report, a binary integer programming was developed and applied for the consulting company to solve the challenge. Later in this report, the reason that this model was selected will be given.This model focuses on optimizing the mix of projects while keeping the total costs, workers and interdepends as constraints. The result of the model showed that 3 projects were selected out of 11. The total costs for selected project was 275,000 euro, which was about 91.67% of the total budgets. In this report, sensitivity analysis was also conducted, it is used to determine how the change of an independent variable will affect the result. Therefore, testing the robustness of the result.
Model FormulationIn this case, we decided to use binary integer linear programming (BILP) rather than other tools to decide the concentration on the projects. The reason we choose integer linear programming is that integer linear programming deals with the optimization of a function of variables and is subject to a set of linear equalities or linear inequalities know as constraints. Model AssumptionsThe following assumptions were made in this formulation. 1. The objective function and the constraint equations are linear2. All coefficients in the objective function and constraint equations are defined with   ddcertainty3. The decision variables are considered to be integer and binary4. The fund is fixed. That is, the total fund available to carry out the selected projects dRis known and fixed. 5. The number of analyst and specialist is fixed. The General BILP  The Binary Integer Liner Programming problem may be stated as:Optimize Z(X),Subject to g(X),WhereX is the binary decision variable which is a zero-one decision vector