Building an ALNS heuristic in Python for vehicle routing, time windows, capacity constraints, and mandatory driver breaks. The post Los Movimientos, Part II: Solving Large Pickup-and-Delivery Problems with Adaptive Large Neighborhood Search appeared first on Towards Data Science .
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.
arXiv:2607. 06066v1 Announce Type: new Abstract: The Vehicle Routing Problem (VRP) and its variants represent some of the most practically consequential optimization challenges in modern logistics and urban mobility.
Using mathematical optimization to solve a pickup-and-delivery problem with time windows. The post “Los Movimientos”: The Routing Problem That Nearly Broke My Spirit appeared first on Towards Data Science .
arXiv:2608. 14156v1 Announce Type: new Abstract: The task of constructing vehicles optimal routes for pickup and delivery of goods is one of most promising tasks in the context of global urban population growth.
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. 06668v1 Announce Type: new Abstract: As an important component of the supply chain industry, transportation has experienced rapid development in the past decade with the assistance of digital platforms and intelligent algorithms.
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:2410.08875v3 Announce Type: replace Abstract: Designing a network (e.g., a telecommunication or transport network) is mainly done offline, in a planning phase, prior to the operation of the net...
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:2609.35443v2 Announce Type: replace Abstract: Large-scale routing problems are difficult to solve efficiently as their search spaces grow rapidly with problem size. Existing approaches primaril...
arXiv:2606. 29725v1 Announce Type: new Abstract: In this paper, we formulate a new vehicle dispatch optimization problem, called Nursing Care Taxi Dispatch, as a variant of the Vehicle Routing Problem, considering constraints related to wheelchair use, user compatibility, pick-up and drop-off times, and vehicle limitations.
The paper introduces Stackelberg Program Optimization (SPO), a framework that uses large language models to discover adaptive destroy‑repair operators for large neighborhood search. SPO conditions operator decisions on a compact state representation, enabling state‑dependent behavior, and frames the discovery process as a Stackelberg game where destroy operators act as leaders and repair operators as conditional followers. Experiments on the traveling salesperson and capacitated vehicle routing problems show that SPO outperforms strong baselines, generalizes to larger instances, and exhibits coupled improvement in operator behavior during discovery.