Introduction | The Saaty AHP and the toy dataset | Individual and Aggregated priorities | Creating pairwise comparison matrices | Individual preference weights | Aggregated preference weights | Aggregated individual judgements | Measuring and visualising consistency | Measuring consistency | Visualising individual priorities and consistency ratios | Dealing with inconsistent and missing data | Identifying inconsistent pairwise comparisons | Finding inconsistent pairwise comparisons by maximum | Transforming inconsistent matrices | Imputing missing pairwise comparison matrices | AHP on steroids: a canned routine | Appendix I: data generation process | References

Dataset | Feature Groupings | Setting a Feasible Target | Solving the Robust Problem | Relaxing robustness to increase the target | Varying the confidence level | Comparison with a Non-Robust Solution | Computation time comparison

Data generating process | Model specification | Solving with standard 'prioritizr' | Solving with 'robust.prioritizr' | Why not just use the worst-case scenario? | Taking the most extreme climate scenario | Adding a buffer to the target | Taking the minimum value across scenarios | Tuning the level of robustness

Introduction | Motivation | Robust minimum set objective | Robust minimum shortfall objective | Conclusion | References