Simulation-based framework for stochastic multi-mode resource-constrained project scheduling

Abstract

This paper introduces a new simulation-based framework designed to tackle the challenges of scheduling projects with uncertain activity durations and limited resources, known as the stochastic multi-mode resource-constrained project scheduling problem (SN-MMRCPSP). By combining Discrete Event Simulation (DES) and Multi-Agent Systems (MAS), the approach captures real-world uncertainties and complex interactions within projects. This model helps decision-makers plan more effectively in uncertain environments.

A Hybrid DES-MAS simulation architecture is proposed to model dynamic, uncertain scheduling environments.

The Taguchi Design of Experiments (DOE) is applied to determine optimal execution modes, enhancing robustness and performance.

Demonstrates the model’s practicality and effectiveness through comprehensive case studies and benchmark comparisons.