Los Movimientos, Part II: Solving Large Pickup-and-Delivery Problems with Adaptive Large Neighborhood Search

A hands-on Python implementation of Adaptive Large Neighborhood Search (ALNS) applied to a real-world pickup-and-delivery vehicle routing problem with time windows, capacity constraints, and mandatory driver rest breaks. The post explains why exact MILP solvers become impractical at scale, then walks through building the full ALNS solution: three destroy operators (random, worst, related removal), two repair operators (greedy and regret-2 insertion), simulated annealing acceptance, and roulette-wheel operator selection. Using the open-source alns Python library, the algorithm reduces the initial objective value by nearly 10x across 5,000 iterations, serving all 24 transportation requests across 6 vehicles while respecting all operational constraints including mandatory roadside breaks for long journeys.

Nguồn: https://towardsdatascience.com/los-movimientos-part-ii-solving-large-pickup-and-delivery-problems-with-adaptive-large-neighborhood-search. 8sync News chỉ tóm tắt và dẫn link; bản quyền nội dung thuộc tác giả và nguồn gốc.