An integrated AHP-GP-GA approach for public project portfolio selection problem

Strategically selecting projects and managing the project portfolio enables firms to enhance their comprehension of project risks and benefits. The capacity to choose a suitable combination of projects is a considerable benefit in the project selection process when confronted with budgetary and other limitations. The selection of projects via an effective methodology is rare, as numerous approaches are considered useless due to constraints on the number of projects available and the inability to identify cost-efficient initiatives. The study presents integrated models of the Analytic Hierarchy Process, Goal Programming, and Genetic Algorithm (AHP-GP-GA) by removing the bias of each model for Public PPSP and building a relationship between the developed models.

The AHP method was utilized to establish project selection criteria, allocate relative priority values to stakeholders, and calculate the overall weighting of project alternatives. The GP employed a computational approach to address numerous goals and limitations. The GA is a suitable mechanism for an efficient and versatile algorithm for optimisation that yields the best possible results. The empirical study demonstrates the fact the integrated approach effectively tackles wide ranging or multiplex issues involving various decision factors, yielding more optimal solutions and exhibiting resilience and adaptability in decision-making problems. The AHP-GP-GA model gives project selection criteria that are more significant in societal sustainability and the Public Project Portfolio Selection Problem (PPSP), has been used to more than 200 large projects, and has been contributed to the literature to improve the current approaches. It also removes the bias in selecting projects.