Tools for multi-criteria decision optimization in multiproject management

Abstract

In today’s highly dynamic business environment and increasingly complex management processes, construction and engineering companies face the challenge of making decisions that must account for a wide range of interrelated criteria. Traditional approaches focused on a single objective – such as minimizing costs or shortening project durations – are becoming ineffective in complex multiproject systems, where each managerial decision has a multidimensional impact on overall performance.

Multi-criteria optimization provides a scientifically grounded framework for reconciling conflicting objectives by combining the flexibility of analytical methods with the precision of mathematical modeling. The integration of Pareto optimality principles, compromise programming, the Analytic Hierarchy Process (AHP), and evolutionary algorithms such as NSGA-II enables the generation of multiple alternative decision options that take into account both short-term operational needs and long-term strategic priorities of an organization.

The practical application of multi-criteria models in multiproject management contributes to the automation of project coordination processes, rational allocation of resources, and reduction of conflicts within corporate ecosystems based on ERP and PPM platforms. Such systems form the foundation for flexible portfolio management, where each project element is integrated into a unified information and analytical space.

The incorporation of cognitive analytics, machine learning, and fuzzy logic enhances the adaptability of management systems and their ability to respond effectively to environmental uncertainty. Multi-criteria optimization emerges as a core tool for building next-generation analytical management models that not only improve the accuracy and resilience of managerial decisions but also lay the groundwork for a transition toward predictive and analytical management in modern multiproject environments.