Open arfff527 opened 5 days ago
Hi,
We applied the proposed method in this repository to an orienteering problem. In this problem, all nodes/customers can be visited, and there exists no infeasible solution to the problem. Only when visiting a customer in its given Time Window, a credit is collected. The ALNS framework makes use of the search operators to find the best possible solution by visiting nodes within their time window. The framework is built upon repair operators that first verify whether a node insertion results in a higher score. In this way, we can handle the time windows in an effective manner. We have also applied the DR-ALNS framework to a CVRP problem with time windows to participate (and win 🥇 :-) ) in a competition (ML4VRP, hosted at GECCO 2023: https://sites.google.com/view/ml4vrp).
Hope that this helps! Robbert
Hi,
I saw that the problem tackled is the 'Orienteering Problem with Stochastic Weights and Time Windows.' Does the code include functionality for handling time windows?
Best Regards, Chu