In the final evaluation on held-out test instances, the method ranked fourth in solution quality and obtained its solution fastest on every instance, with an average runtime of 9.0 seconds compared to 118.8 seconds for the next-fastest submission.
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 changes to a road network would make a route chosen by the user the optimal route. This enables explanations such as"Your suggested route would indeed have been optimal, if road X were not a bicycle path."Our solution models the problem as an integer program, iteratively incorporating constraints until an exact solution is found. In the final evaluation on held-out test instances, our method ranked fourth in solution quality and obtained its solution fastest on every instance, with an average runtime of 9.0 seconds compared to 118.8 seconds for the next-fastest submission.
This work modeled the SNMP as a Pickup and Delivery Problem on an expanded graph with an ordered structure and solved it via a branch-and-price algorithm, using a labeling algorithm with two distinct dominance rules.
V. Nascimento, Luidi Simonetti· Journal of combinatorial opt...· 0 citations
This paper studies joint sampling, route activation, and preemption control over $N$ heterogeneous transmission routes under a long-run objective combining Age of Information (AoI) with sampling and transmission costs. We formulate the problem as an average-cost impulse-control model, derive a vector-form integral aver...
This paper analyses the Stochastic Team Orienteering Problem (STOP), a stochastic variant of the Team Orienteering Problem (TOP). In the STOP, travel times are represented by random variables. The objective is to determine a set of routes that maximises the expected collected profit. We model the problem as a two-stage...
Alberto Guastalla, Jean-François Côté, R. Aringhieri· 0 citations
The backhaul profit maximization problem (BPMP), which is known to be NP-hard, requires simultaneously solving two problems: (1)
determining how to route an empty delivery vehicle back from its current location to its depot by a scheduled arrival time, and (2) selecting
a profit-maximizing subset of spot-market deliver...
Lam Tran, Daniel Ryan, E. Olinick et al.· IISE Annual Conference &...· 0 citations
The quickest path reliability problem is to compute the probability that a given flow is transmitted along a single source-destination path within a given time limit. When a budget is imposed, path feasibility is jointly dependent on lead time, transmission cost, and capacity. Existing exact methods may require enumera...
In autonomous mobility duopolies, platforms compete for riders based on vehicle proximity. A critical operational challenge---faced by an incumbent proactively defending against a market entrant---is how to dispatch fleets to minimize demand poached by a reactive competitor. We model this competition as a zero-sum robo...
Ioannis Caragiannis, Kostas Kollias, M. Roghani et al.· 0 citations
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MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
