no code implementations • 22 Oct 2023 • Abhay Sobhanan, Junyoung Park, Jinkyoo Park, Changhyun Kwon
For each higher-level decision candidate, we predict the objective function values of the underlying vehicle routing problems using a pre-trained graph neural network without actually solving the routing problems.
no code implementations • 14 Jul 2023 • Sasan Mahmoudinazlou, Changhyun Kwon
This paper proposes a hybrid genetic algorithm for solving the Multiple Traveling Salesman Problem (mTSP) to minimize the length of the longest tour.
1 code implementation • 29 Jun 2023 • Hyeonah Kim, Jinkyoo Park, Changhyun Kwon
We design a learning-based separation heuristic algorithm with graph coarsening that learns the solutions of the exact separation problem with a graph neural network (GNN), which is trained with small instances of 50 to 100 customers.
no code implementations • 1 Mar 2023 • Sasan Mahmoudinazlou, Changhyun Kwon
This study presents a hybrid genetic algorithm for solving TSPD and FSTSP by incorporating local search and dynamic programming.
1 code implementation • 22 Dec 2021 • Aigerim Bogyrbayeva, Taehyun Yoon, Hanbum Ko, Sungbin Lim, Hyokun Yun, Changhyun Kwon
Reinforcement learning has recently shown promise in learning quality solutions in many combinatorial optimization problems.
no code implementations • 29 Sep 2021 • Aigerim Bogyrbayeva, Taehyun Yoon, Hanbum Ko, Sungbin Lim, Hyokun Yun, Changhyun Kwon
State-less attention-based decoder fails to make such coordination between vehicles.
1 code implementation • 5 Oct 2020 • Aigerim Bogyrbayeva, Sungwook Jang, Ankit Shah, Young Jae Jang, Changhyun Kwon
This paper proposes a reinforcement learning approach for nightly offline rebalancing operations in free-floating electric vehicle sharing systems (FFEVSS).