Petri Nets based Iterative Validation of Prescriptive MILP Models: A Case Study in Offshore Installation Scheduling

Effective resource and task scheduling is crucial for operational efficiency in offshore installation projects. Although Mixed Integer Linear Programming (MILP) models are commonly utilized for prescriptive scheduling, they often lack comprehensive validation. This study introduces an iterative validation framework that integrates Petri nets (PNs) and process mining to validate MILP models, specifically applied to Offshore Wind Farm (OWF) installations. The proposed methodology enables cross-validation through PNs derived from MILP solutions, facilitating robust verification of the scheduling output. The practical applicability and computational complexity of this iterative approach are demonstrated through an extensive numerical case study, highlighting significant improvements in validation practices for industrial scheduling challenges.