14 citations · 23 across the 9 of their papers we have counts for
9 papers
Adaptive Bias Generalized Rollout Policy Adaptation on the Flexible Job-Shop Scheduling Problem
Lotfi Kobrosly, Marc-Emmanuel Coupvent des Graviers, Christophe Guettier +1
The Flexible Job-Shop Scheduling Problem (FJSSP) is an NP-hard combinatorial optimization problem, with several application domains, especially for manufacturing purposes. The obje…
Updating Lower and Upper Bounds for the Job-Shop Scheduling Problem Test Instances
Marc-Emmanuel Coupvent des Graviers, Lotfi Kobrosly, Christophe Guettier +1
The Job-Shop Scheduling Problem (JSSP) and its variant, the Flexible Job-Shop Scheduling Problem (FJSSP), are combinatorial optimization problems studied thoroughly in the literatu…
Sensor Allocation and Online-Learning-based Path Planning for Maritime Situational Awareness Enhancement: A Multi-Agent Approach
Bach Long Nguyen, Anh-Dzung Doan, Tat-Jun Chin +5
Countries with access to large bodies of water often aim to protect their maritime transport by employing maritime surveillance systems. However, the number of available sensors (e…
Planning and Learning: Path-Planning for Autonomous Vehicles, a Review of the Literature
Kevin Osanlou, Christophe Guettier, Tristan Cazenave +1
This short review aims to make the reader familiar with state-of-the-art works relating to planning, scheduling and learning. First, we study state-of-the-art planning algorithms.…
Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability using Tree Search and Graph Neural Networks
Kevin Osanlou, Jeremy Frank, Andrei Bursuc +4
Planning under uncertainty is an area of interest in artificial intelligence. We present a novel approach based on tree search and graph machine learning for the scheduling problem…
Learning-based Preference Prediction for Constrained Multi-Criteria Path-Planning
Kevin Osanlou, Christophe Guettier, Andrei Bursuc +2
Learning-based methods are increasingly popular for search algorithms in single-criterion optimization problems. In contrast, for multiple-criteria optimization there are significa…
Time-based Dynamic Controllability of Disjunctive Temporal Networks with Uncertainty: A Tree Search Approach with Graph Neural Network Guidance
Kevin Osanlou, Jeremy Frank, J. Benton +4
Scheduling in the presence of uncertainty is an area of interest in artificial intelligence due to the large number of applications. We study the problem of dynamic controllability…
Constrained Shortest Path Search with Graph Convolutional Neural Networks
Kevin Osanlou, Christophe Guettier, Andrei Bursuc +2
Planning for Autonomous Unmanned Ground Vehicles (AUGV) is still a challenge, especially in difficult, off-road, critical situations. Automatic planning can be used to reach missio…
Optimal Solving of Constrained Path-Planning Problems with Graph Convolutional Networks and Optimized Tree Search
Kevin Osanlou, Andrei Bursuc, Christophe Guettier +2
Deep learning-based methods are growing prominence for planning purposes. In this paper, we present a hybrid planner that combines a graph machine learning model and an optimal sol…