A Metaheuristic Approach for IT Projects Portfolio Optimization

TL;DR

This paper introduces a genetic algorithm-based metaheuristic for optimizing multi-period IT project portfolios, considering interdependencies, budget constraints, and sequencing, aiding managers in strategic funding decisions.

Contribution

It presents a novel mathematical model combined with a genetic algorithm to optimize multi-stage IT project portfolios with interdependencies and sequencing constraints.

Findings

The model effectively optimizes portfolio value within constraints.

The genetic algorithm provides flexible solutions for project sequencing.

Managers can generate alternative portfolios by adjusting project number constraints.

Abstract

Optimal selection of interdependent IT Projects for implementation in multi periods has been challenging in the framework of real option valuation. This paper presents a mathematical optimization model for multi-stage portfolio of IT projects. The model optimizes the value of the portfolio within a given budgetary and sequencing constraints for each period. These sequencing constraints are due to time wise interdependencies among projects. A Metaheuristic approach is well suited for solving this kind of a problem definition and in this paper a genetic algorithm model has been proposed for the solution. This optimization model and solution approach can help IT managers taking optimal funding decision for projects prioritization in multiple sequential periods. The model also gives flexibility to the managers to generate alternative portfolio by changing the maximum and minimum number of projects to be implemented in each sequential period.