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New integer programming method excels in counterfactual routing competition

Researchers have developed a novel approach for the Counterfactual Routing Competition (CRC 25) by modeling the problem as an integer program with iterative constraint generation. This method aims to find the minimal changes needed in a road network to make a user's chosen route the optimal one, providing explanations like "Your suggested route would indeed have been optimal, if road X were not a bicycle path." In the competition's final evaluation, this solution achieved fourth place in solution quality and was the fastest, with an average runtime of 9.0 seconds compared to the next-fastest submission's 118.8 seconds. AI

IMPACT This research demonstrates an advanced method for generating counterfactual explanations in routing problems, potentially improving user understanding and trust in navigation systems.

RANK_REASON Submission to an academic competition detailing a novel method for a specific problem. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New integer programming method excels in counterfactual routing competition

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Submission to an academic competition detailing a novel method for a specific problem. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Dani\"el Vos, Sterre Lutz ·

    Counterfactual Routing Using Integer Programming with Constraint Generation

    arXiv:2609.03707v1 Announce Type: new Abstract: We present our submission to the IJCAI 2025 'Counterfactual Routing Competition' (CRC 25). The goal of the competition is to find counterfactual explanations for the shortest path problem. This requires deciding what the minimal cha…