Emmanuel Hebrard
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Emmanuel Hebrard has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Christian Artigues
LAAS-CNRS Université de Toulouse CNRS Toulouse France
3 shared publications - Julien Rouzot
Univ Toulouse, CNRS, LAAS
2 shared publications - Pierre Lopez
LAAS-CNRS, Université de Toulouse, CNRS
2 shared publications - Bertrand Simon
IN2P3 Computing Center CNRS Villeurbanne France
1 shared publication - Clément Carbonnel
University of Montpellier, CNRS, LIRMM
1 shared publication - Cyrille Briand
LAAS-CNRS Université de Toulouse CNRS Toulouse France
1 shared publication
Latest Publications
- 1 June 2026
- Published by Springer Nature
- p. 470-485
Scheduling Data Transfers with Priorities for Space Missions
- 1 June 2026
- Published by Springer Nature
- p. 470-485
Scheduling Data Transfers with Priorities for Space Missions
- Open Access
Hierarchical Rectangle Packing Solved by Multi-Level Recursive Logic-based Benders Decomposition
We study the two-dimensional hierarchical rectangle packing problem, motivated by applications in analog integrated circuit layout, facility layout, and logistics. Unlike classical strip or bin packing, the dimensions of the container are not fixed, and the packing is inherently hierarchical: each item is either a rectangle or a block occurrence, whose dimensions are a solution of another packing problem. This recursive structure reflects real-world scenarios in which components, boxes, or modules must be packed within higher-level containers. We formally define the problem and propose exact formulations in Mixed-Integer Linear Programming and Constraint Programming. Given the computational difficulty of solving complex packing instances directly, we propose decomposition heuristics. First, we implement an existing Bottom-Up baseline method that solves subblocks before combining them at higher levels. Building upon this, we introduce a novel multilevel Logic-based Benders Decomposition method. This heuristic method dynamically refines block dimension constraints, eliminating the need for manual selection of candidate widths or aspect ratios. Experiments on synthetic instances with up to seven hierarchy levels, 80 items per block, and limited computation time show that the proposed decomposition significantly outperforms both monolithic formulations and the Bottom-Up method in terms of solution quality and scalability.
Open AccessHierarchical Rectangle Packing Solved by Multi-Level Recursive Logic-based Benders Decomposition
We study the two-dimensional hierarchical rectangle packing problem, motivated by applications in analog integrated circuit layout, facility layout, and logistics. Unlike classical strip or bin packing, the dimensions of the container are not fixed, and the packing is inherently hierarchical: each item is either a rectangle or a block occurrence, whose dimensions are a solution of another packing problem. This recursive structure reflects real-world scenarios in which components, boxes, or modules must be packed within higher-level containers. We formally define the problem and propose exact formulations in Mixed-Integer Linear Programming and Constraint Programming. Given the computational difficulty of solving complex packing instances directly, we propose decomposition heuristics. First, we implement an existing Bottom-Up baseline method that solves subblocks before combining them at higher levels. Building upon this, we introduce a novel multilevel Logic-based Benders Decomposition method. This heuristic method dynamically refines block dimension constraints, eliminating the need for manual selection of candidate widths or aspect ratios. Experiments on synthetic instances with up to seven hierarchy levels, 80 items per block, and limited computation time show that the proposed decomposition significantly outperforms both monolithic formulations and the Bottom-Up method in terms of solution quality and scalability.
- 29 June 2025
- Published by Springer Nature
- p. 173-190
Integer and Constraint Programming for the Offline Nanosatellite Partition Scheduling Problem
- 29 June 2025
- Published by Springer Nature
- p. 173-190
Integer and Constraint Programming for the Offline Nanosatellite Partition Scheduling Problem