A review on learning to solve combinatorial optimisation problems in manufacturing
An efficient manufacturing system is key to maintaining a healthy economy today. With the
rapid development of science and technology and the progress of human society, the …
rapid development of science and technology and the progress of human society, the …
Learning to search feasible and infeasible regions of routing problems with flexible neural k-opt
In this paper, we present Neural k-Opt (NeuOpt), a novel learning-to-search (L2S) solver for
routing problems. It learns to perform flexible k-opt exchanges based on a tailored action …
routing problems. It learns to perform flexible k-opt exchanges based on a tailored action …
Glop: Learning global partition and local construction for solving large-scale routing problems in real-time
The recent end-to-end neural solvers have shown promise for small-scale routing problems
but suffered from limited real-time scaling-up performance. This paper proposes GLOP …
but suffered from limited real-time scaling-up performance. This paper proposes GLOP …
Reinforced Lin–Kernighan–Helsgaun algorithms for the traveling salesman problems
Abstract The Traveling Salesman Problem (TSP) is a classical NP-hard combinatorial
optimization problem with many practical variants. The Lin–Kernighan–Helsgaun (LKH) …
optimization problem with many practical variants. The Lin–Kernighan–Helsgaun (LKH) …
Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives
Although several surveys on Neural Combinatorial Optimization (NCO) solvers specifically
designed to solve Vehicle Routing Problems (VRPs) have been conducted. These existing …
designed to solve Vehicle Routing Problems (VRPs) have been conducted. These existing …
A reinforced hybrid genetic algorithm for the traveling salesman problem
We propose a new method called the Reinforced Hybrid Genetic Algorithm (RHGA) for
solving the famous NP-hard Traveling Salesman Problem (TSP). Specifically, we combine …
solving the famous NP-hard Traveling Salesman Problem (TSP). Specifically, we combine …
Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment Problem
Recently various optimization problems, such as Mixed Integer Linear Programming
Problems (MILPs), have undergone comprehensive investigation, leveraging the …
Problems (MILPs), have undergone comprehensive investigation, leveraging the …
[HTML][HTML] The first AI4TSP competition: Learning to solve stochastic routing problems
This paper reports on the first international competition on AI for the traveling salesman
problem (TSP) at the International Joint Conference on Artificial Intelligence 2021 (IJCAI-21) …
problem (TSP) at the International Joint Conference on Artificial Intelligence 2021 (IJCAI-21) …
NeuralGLS: learning to guide local search with graph convolutional network for the traveling salesman problem
J Sui, S Ding, B Xia, R Liu, D Bu - Neural Computing and Applications, 2024 - Springer
The traveling salesman problem (TSP) aims to find the shortest tour that visits each node of
a given graph exactly once. TSPs have significant importance as numerous practical …
a given graph exactly once. TSPs have significant importance as numerous practical …
Mejora de las soluciones del problema del viajante múltiple mediante técnicas de aprendizaje automático y optimización de Harris Hawks
AA Hussein, MA Hameed, SH Ahmed - Revista Científica de …, 2024 - 209.45.90.234
Este trabajo presenta un enfoque para resolver el Problema del Viajante Múltiple (mTSP)
mediante la integración de algoritmos metaheurísticos (MHs) con técnicas de aprendizaje …
mediante la integración de algoritmos metaheurísticos (MHs) con técnicas de aprendizaje …