Robust optimization for multi-project scheduling via the critical chain method
Min Tian, Xiaomei Li
TL;DR
This paper improves multi-project scheduling by enhancing the critical chain method with new robustness measures and a better algorithm.
Contribution
A new robustness measure and discrete differential evolution algorithm for multi-project scheduling using the critical chain method.
Findings
The proposed robustness measure improves scheduling stability and reduces buffer overflow.
The enhanced discrete DE algorithm outperforms benchmarks by over 3.3% in robustness.
The new method effectively balances resource constraints across sub-projects.
Abstract
The critical chain method is often used to improve robustness in single-project scheduling, but there are two challenges when applying it to multi-project scheduling. First, the existing robustness measure focuses on time elasticity within sub-projects but neglects elasticity across sub-projects, making it difficult to balance drum resource requirements. Second, the differential evolution (DE) algorithm is adopted to solve this problem, but continuous evolutionary operators have limited flexibility, leading to numerous transformations between the continuous solution space and the discrete problem space. Therefore, we adjust the critical chain multi-project scheduling model by incorporating the drum buffer and the capacity constraint buffer and propose a robustness measure that considers both time elasticity within and among sub-projects. Meanwhile, we design an enhanced discrete DE…
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Taxonomy
TopicsResource-Constrained Project Scheduling · Advanced Multi-Objective Optimization Algorithms · Process Optimization and Integration