Extending Resource Constrained Project Scheduling to Mega-Projects with Model-Based Systems Engineering & Hetero-functional Graph Theory

TL;DR

This paper integrates resource-constrained project scheduling with model-based systems engineering and hetero-functional graph theory, enabling better analysis, monitoring, and control of complex megaprojects through a unified formal framework.

Contribution

It develops a systematic translation from project networks to SysML diagrams and hetero-functional graphs, extending RCPSP to complex systems with explicit project state explanations.

Findings

Specialized hetero-functional network formulation for RCPSP

Explicit project state explanations improve monitoring

Framework accommodates real-world constraints in megaprojects

Abstract

Within the project management context, project scheduling serves as an indispensable component, functioning as a fundamental tool for planning, monitoring, controlling, and managing projects more broadly. Although the resource-constrained project scheduling problem (RCPSP) lies at the core of project management activities, it remains largely disconnected from the broader literature on model-based systems engineering (MBSE), thereby limiting its integration into the design and management of complex systems. The original contribution of this paper is twofold. First, the paper seeks to reconcile the RCPSP with the broader literature and vocabulary of model-based systems engineering and hetero-functional graph theory (HFGT). A concrete translation pipeline from an activity-on-node network to a SysML activity diagram, and then to an operand net is constructed. Using this representation, it specializes the hetero-functional network minimum-cost flow (HFNMCF) formulation to the RCPSP context as a systematic means of HFGT for quantitative analysis and proves that the RCPSP is recoverable as a special case of a broader model. Secondly, on an illustrative instance with renewable and non-renewable operands, the specialized HFNMCF, while producing similar schedules, yields explicit explanations of the project states that enable richer monitoring and control. Overall, the framework preserves the strengths of the classical RCPSP while accommodating real-world constraints and enterprise-level decision processes encountered in large, complex megaprojects.