# MultiZenoTravel: a Tunable Benchmark for Multi-Objective Planning with Known Pareto Front

arXiv: https://arxiv.org/abs/2304.14659 · HTML: https://mlsanity.com/paper/2304.14659/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 15 references that are in the map.
- First posted on arXiv 28 Apr 2023.

## Builds on (most cited first, 2 of 2)

- [From Classical to Hierarchical: benchmarks for the HTN Track of the International Planning Competition](https://mlsanity.com/paper/2103.05481/) (2021)
- [Exploring Instance Generation for Automated Planning](https://mlsanity.com/paper/2009.10156/) (2020)

## Abstract (arXiv)

Multi-objective AI planning suffers from a lack of benchmarks exhibiting known Pareto Fronts. In this work, we propose a tunable benchmark generator, together with a dedicated solver that provably computes the true Pareto front of the resulting instances. First, we prove a proposition allowing us to characterize the optimal plans for a constrained version of the problem, and then show how to reduce the general problem to the constrained one. Second, we provide a constructive way to find all the Pareto-optimal plans and discuss the complexity of the algorithm. We provide an implementation that allows the solver to handle realistic instances in a reasonable time. Finally, as a practical demonstration, we used this solver to find all Pareto-optimal plans between the two largest airports in the world, considering the routes between the 50 largest airports, spherical distances between airports and a made-up risk.