Self-Guiding Exploration for Combinatorial Problems

Z Iklassov, Y Du, F Akimov, M Takac - arXiv preprint arXiv:2405.17950, 2024 - arxiv.org
Large Language Models (LLMs) have become pivotal in addressing reasoning tasks across
diverse domains, including arithmetic, commonsense, and symbolic reasoning. They utilize …

Reinforcement Learning for Solving Stochastic Vehicle Routing Problem with Time Windows

Z Iklassov, I Sobirov, R Solozabal, M Takac - arXiv preprint arXiv …, 2024 - arxiv.org
This paper introduces a reinforcement learning approach to optimize the Stochastic Vehicle
Routing Problem with Time Windows (SVRP), focusing on reducing travel costs in goods …

Curriculum Generation for Learning Guiding Functions in State-Space Search Algorithms

S Pendurkar, LHS Lelis, NR Sturtevant… - Proceedings of the …, 2024 - ojs.aaai.org
This paper investigates methods for training parameterized functions for guiding state-space
search algorithms. Existing work commonly generates data for training such guiding …

Learning to Solve Job Shop Scheduling Under Uncertainty

G Infantes, S Roussel, P Pereira, A Jacquet… - … Conference on the …, 2024 - Springer
Abstract Job-Shop Scheduling Problem (JSSP) is a combinatorial optimization problem
where tasks need to be scheduled on machines in order to minimize criteria such as …

[图书][B] Integration of Constraint Programming, Artificial Intelligence, and Operations Research

B Dilkina - 2024 - books.google.com
This book constitutes the proceedings of the 21st International Conference on the Integration
of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2024 …

Implementation Of Reinforcement Learning To Solve Job-Shop Scheduling Problem

R Maharjan - 2024 - uia.brage.unit.no
The Job Shop Scheduling Problem (JSSP) consists of allocating various tasks to distinct
machines, each of which has a different sequence of operations. This thesis investigates the …