Bridging the Evaluation Gap: Standardized Benchmarks for Multi-Objective Search
Empirical evaluation in multi-objective search (MOS) has historically suffered from fragmentation, relying on heterogeneous problem instances with incompatible objective definitions that make cross-study comparisons difficult. This standardization gap is further exacerbated by the realization that DIMACS road networks, a historical default benchmark for the field, exhibit highly correlated objectives that fail to capture diverse Pareto-front structures. To address this, we introduce the first comprehensive, standardized benchmark suite for exact and approximate MOS. Our suite spans four structurally diverse domains: real-world road networks, structured synthetic graphs, game-based grid en...
| Authors | Hadar Peer, Carlos Hernandez, Sven Koenig et al. |
|---|---|
| Primary category | cs.AI |
| Published | 25 March 2026 |
| Last updated at source | 9 August 2026 |
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