arXiv:2503. 03137v3 Announce Type: replace Abstract: Constructive neural combinatorial optimization (NCO) offers a promising paradigm for solving vehicle routing problems (VRPs) by directly learning to construct approximate optimal solutions, thereby reducing reliance on expert knowledge for algorithm design.
arXiv:2607. 03694v1 Announce Type: new Abstract: Large-scale Capacitated Vehicle Routing Problems (CVRPs) are commonly solved by partitioning customers into smaller routing problems that can be optimized independently.
arXiv:2602. 23092v2 Announce Type: replace Abstract: The Capacitated Vehicle Routing Problem (CVRP), a fundamental combinatorial optimization challenge, focuses on optimizing fleet operations under vehicle capacity constraints.
arXiv:2608. 14140v1 Announce Type: new Abstract: The problem of route optimization with realistic constraints is becoming extremely relevant in the face of global urban population growth.
The paper introduces COMPASS, an algorithm for the Ordered Clustered Traveling Salesman Problem (OCTSP) that combines search with learning-accelerated routing through parallel sub-solvers. COMPASS improves solutions continuously with more compute, exploits clustered structure to achieve exact solutions in time exponential in cluster size, and outperforms existing methods. It works with general distance matrices, not just coordinate inputs, and scales to 100,000 synthetic nodes and 28,500 real e-commerce nodes, representing the largest reported routing solution over asymmetric distances.
COMPASS is a new algorithm for the Ordered Clustered Traveling Salesman Problem (OCTSP) that combines search with learning‑accelerated routing by orchestrating parallel sub‑solvers. It exploits the clustered structure to achieve exact solutions in time exponential in cluster size rather than instance size, and its solutions improve continuously with more compute. Empirically, COMPASS outperforms existing methods and scales to 100K synthetic nodes and 28.5K real e‑commerce nodes, representing the largest reported routing solution over asymmetric distances—9× beyond established ATSP benchmarks.
arXiv:2606. 31820v1 Announce Type: new Abstract: Large-scale capacitated vehicle routing problems (CVRPs) are commonly addressed using cluster-first route-second (CFRS) approaches that split a routing instance into smaller, computationally tractable subproblems.
arXiv:2405. 01906v3 Announce Type: replace Abstract: In modern intelligent transportation systems (ITS), particularly in freight transportation and logistics, real-time route planning is crucial.
SynthCharge is a parametric generator that creates diverse, feasibility‑screened instances of the electric vehicle routing problem with time windows (EVRPTW). It produces instances ranging from 5 to 100 customers (up to 500 in theory) with adaptive energy capacity scaling and range‑aware charging station placement, filtering out unsolvable cases via a fast feasibility screening process. This dynamic benchmarking infrastructure enables systematic evaluation of learning‑based routing and data‑driven approaches.
arXiv:2602. 07216v2 Announce Type: replace Abstract: Neural combinatorial optimization (NCO) trains fast heuristics for routing problems, but planners often need more than a single solve: they ask which stop to drop, which transition to preserve, or which subset of stops to remove if a route is infeasible.
arXiv:2607. 22356v1 Announce Type: new Abstract: In recent years, the growing complexity of last-mile pickup operations has increased the need for fast and accurate decision-making on logistics platforms.
arXiv:2609.26275v1 Announce Type: new Abstract: The vehicle routing problems with real-world constraints (we consider vehicles capacity limits, time windows constrains, pickup-and-delivery multi-depo...