Trustworthy Planning and Scheduling with Learning and Explanations

Livrables

GitHub/TUPLES lab - simulators & planning domains

Use case simulators and planning domains hosted on GitHub/TUPLES lab (M18, Software).

Fram. learning with robustness guarantees

Framework for policy learning with decision-robustness guarantees (M18, Software).

Expl. ML models and systems of constraints

Explanations for ML models and systems of constraints (M12, Report+Software).

Fram. for robustness verification of policies

Framework for robustness verification of policy-decisions (M18, Software).

Expl. policies in non-learning based P&S

Explanations for action policies in non-learning based scheduling and planning (M18, Report+Software).

Methods for integration of LRNNs into P&S

Methods for integration of LRNNs into planning and scheduling domains (M18, software, report)

Integrated online/offline (re-)scheduling

Integrated offline/online scheduling and rescheduling solutions (M18, Report).

Robust integration of learning and solving

Robust integrated learning and solving with predicted costs (M18, Report).

Publications

Safe Reinforcement Learning Through Regret and State Restorations in Evaluation Stages

Auteurs: Timo P. Gros, Nicola J. Müller, Daniel Höller, Verena Wolf
Publié dans: Proceedings of the Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS), at ICAPS'24, 2024
Éditeur: http://fai.cs.uni-saarland.de/gros/papers/icaps24-RDDPS.pdf

Faster Robustness Verification by Exploiting Repeated Structure in Adversarial Examples

Auteurs: Lorenzo Cascioli, Laurens Devos, Jesse Davis
Publié dans: Proceedings of the ECAI Workshop on Verifying Learning AI Systems (VeriLearn'23), 2023

Faster Repeated Evasion Attacks in Tree Ensembles

Auteurs: Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis
Publié dans: Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 2024
Éditeur: Curran Associates, Inc.; https://papers.nips.cc/paper_files/paper/2024

Conversational Goal-Conflict Explanations in Planning via Multi-Agent LLMs

Auteurs: Guilhem Fouilhé, Rebecca Eifler, Antonin Poché, Sylvie Thiébaux, Nicholas Asher
Publié dans: Proceedings of the AAAI25 Workshop on Planning in the Era of LLMs (LM4Plan@AAAI-25), 2025
Éditeur: Openreview

Detecting Evasion Attacks in Deployed Tree Ensembles

Auteurs: Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis
Publié dans: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD'23), 2023, ISBN 978-3-031-43424-2
Éditeur: Springer
DOI: 10.1007/978-3-031-43424-2_8

An Efficient Structured Perceptron for NP-Hard Combinatorial Optimization Problems

Auteurs: Bastián Véjar, Gaël Aglin, Ali İrfan Mahmutoğulları, Siegfried Nijssen, Pierre Schaus, Tias Guns
Publié dans: Lecture Notes in Computer Science, Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2024
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-60599-4_17

Learning Heuristics for Numeric Planning

Auteurs: Dillon Z Chen and Sylvie Thiebaux
Publié dans: Proceedings of the 37th Annual Conference on Neural Information Processing Systems (NeurIPS-24), 2024
Éditeur: Curran Associates

On Picking Good Policies: Leveraging Action-Policy Testing in Policy Training

Auteurs: Jan Eisenhut, Daniel Fišer, Isabel Valera, Jörg Hoffmann
Publié dans: Proceedings of the 35th International Conference on Automated Planning and Scheduling (ICAPS'25), 2025
Éditeur: AAAI Press

Action Policy Testing with Heuristic-Based Bias Functions

Auteurs: Xandra Schuler, Jan Eisenhut, Daniel Höller, Daniel Fišer and Jörg Hoffmann
Publié dans: Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS'23), 2023
Éditeur: none

Multi-class Robustness Verification for Tree Ensembles

Auteurs: Laurens Devos, Lorenzo Cascioli, Jesse Davis
Publié dans: Proceedings of the ECAI Workshop on Verifying Learning AI Systems Workshop (VeriLearn'23), 2023

Safety Verification of Tree-Ensemble Policies via Predicate Abstraction

Auteurs: Chaahat Jain, Lorenzo Cascioli, Laurens Devos, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jörg Hoffmann
Publié dans: Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS'24), 2024, ISBN 978-1-64368-548-9
Éditeur: None
DOI: 10.3233/FAIA240614

Neural Policy Safety Verification via Predicate Abstraction: CEGAR

Auteurs: Marcel Vinzent, Siddhant Sharma, Jörg Hoffmann
Publié dans: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI'23), 2023, ISSN 2374-3468
Éditeur: AAAI Press
DOI: 10.1609/aaai.v37i12.26772

Simplifying Step-wise Explanation Sequences

Auteurs: Ignace Bleukx, Jo Devriendt, Emilio Gamba, Bart Bogaerts, Tias Guns
Publié dans: Proceedings of the 29th International Conference on Principles and Practice of Constraint Programming (CP'23), 2023, ISSN 1868-8969
Éditeur: Leibniz-Zentrum für Informatik

Towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches

Auteurs: Léo Boisvert, Hélène Verhaeghe, Quentin Cappart
Publié dans: Lecture Notes in Computer Science, Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2024
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-60597-0_7

Guided Bottom-Up Interactive Constraint Acquisition

Auteurs: Dimosthenis Tsouros, Senne Berden, Tias Guns
Publié dans: Proceedings of the 29th International Conference on Principles and Practice of Constraint Programming (CP'23), 2023, ISSN 1868-8969
Éditeur: Leibniz-Zentrum für Informatik
DOI: 10.48550/arXiv.2307.06126

Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal

Auteurs: Leah Chrestien, Stefan Edelkamp, Antonin Komenda, Tomas Pevny
Publié dans: Proceedings of the 37th Annual Conference on Neural Information Processing Systems (NeurIPS'23), 2023
Éditeur: none

Blossom: an Anytime Algorithm for Computing Optimal Decision Trees

Auteurs: Emir Demirović, Emmanuel Hebrard, Louis Jean
Publié dans: Proceedings of the 40th International Conference on Machine Learning (ICML'23), 2023
Éditeur: PMLR

Computational Asymmetries in Robust Classification

Auteurs: Samuele Marro, Michele Lombardi.
Publié dans: Proceedings of the 40th International Conference on Machine Learning (ICML'23), 2023
Éditeur: ICML
DOI: 10.48550/arXiv.2306.14326

Policy-Specific Abstraction Predicate Selection in Neural Policy Safety Verification

Auteurs: Marcel Vinzent, Min Wu, Haoze Wu, Jörg Hoffmann
Publié dans: Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS'23), 2023
Éditeur: none

Is This a Good Decision? Action Optimality Checking in Classical Planning

Auteurs: Jan Eisenhut, Daniel Fišer, Wheeler Ruml, Jörg Hoffmann
Publié dans: Proceedings of the 28th European Conference on Artificial Intelligence (ECAI'25), 2025
Éditeur: IOS Press

Explaining the Space of SSP Policies via Policy-Property Dependencies: Complexity, Algorithms, and Relation to Multi-Objective Planning

Auteurs: Marcel Steinmetz, Sylvie Thiébaux, Daniel Höller, and Florent Teichteil-Königsbuch
Publié dans: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Éditeur: AAAI Press

Disjunctive Scheduling in Tempo

Auteurs: Emmanuel Hebrard
Publié dans: Proceedings of the 31st International Conference on Principles and Practice of Constraint Programming (CP-25)), 2025
Éditeur: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
DOI: 10.4230/LIPICS.CP.2025.13

Policy Safety Testing in Non-Deterministic Planning: Fuzzing, Test Oracles, Fault Analysis

Auteurs: Chaahat Jain, Daniel Sherbakov, Marcel Vinzent, Marcel Steinmetz, Jesse Davis and Jörg Hoffmann
Publié dans: Proceedings of the 28th European Conference on Artificial Intelligence (ECAI'25), 2025
Éditeur: IOS Press

Learning to Learn in Interactive Constraint Acquisition

Auteurs: Dimosthenis Tsouros, Senne Berden, Tias Guns
Publié dans: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024, ISSN 2159-5399
Éditeur: AAAI Press, Washington, DC, USA
DOI: 10.1609/aaai.v38i8.28655

ReDeLEx: A Framework for Relational Deep Learning Exploration

Auteurs: Jakub Peleska, Gustav Sir
Publié dans: Lecture Notes in Artificial Intelligence, 2025
Éditeur: Springer

An Operator-Centric Trustable Decision-Making Tool for Planning Ground Logistic Operations of Beluga Aircraft

Auteurs: Rebecca Eifler, Nika Beriachvili, Arthur Bit-Monnot, Dillon Z. Chen, Jan Eisenhut, Joerg Hoffmann, Sylvie Thiébaux, and Florent Teichteil-Königsbuch
Publié dans: Proceedings of the 28th European Conference on Artificial Intelligence (ECAI-25), Demonstration Track, 2025
Éditeur: IOS Press

Exploiting Symmetries in MUS Computation

Auteurs: Ignace Bleukx, Hélène Verhaeghe, Bart Bogaerts, Tias Guns
Publié dans: Proceedings of the AAAI Conference on Artificial Intelligence, Numéro 39, 2025, ISSN 2374-3468
Éditeur: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I11.33209

Modeling and Explaining an Industrial Workforce Allocation and Scheduling Problem

Auteurs: Ignace Bleukx, Ryma Boumazouza, Tias Guns, Nadine Laage, Guillaume Poveda
Publié dans: Proceedings of the 31st International Conference on Principles and Practice of Constraint Programming (CP-25), 2025
Éditeur: Dagstuhl Publishing
DOI: 10.4230/LIPICS.CP.2025.6

Decision-Focused Learning to Predict Action Costs for Planning

Auteurs: Jayanta Mandi, Marco Foschini, Daniel Höller, Sylvie Thiebaux, Jörg Hoffmann, Tias Guns
Publié dans: Frontiers in Artificial Intelligence and Applications, ECAI 2024, 2024
Éditeur: IOS Press
DOI: 10.3233/FAIA240975

Learning Domain-Independent Heuristics for Grounded and Lifted Planning

Auteurs: Dillon Z. Chen, Sylvie Thiébaux, Felipe Trevizan
Publié dans: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024, ISSN 2159-5399
Éditeur: AAAI Press
DOI: 10.1609/aaai.v38i18.29986

New Fuzzing Biases for Action Policy Testing

Auteurs: Jan Eisenhut, Xandra Schuler, Daniel Fišer, Daniel Höller, Maria Christakis, Jörg Hoffmann
Publié dans: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Éditeur: AAAI Press

Guiding GBFS through Learned Pairwise Rankings

Auteurs: Mingyu Hao, Felipe Trevizan, Sylvie Thiebaux, Patrick Ferber and Jörg Hoffmann
Publié dans: Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), 2024
Éditeur: IJCAI Organization
DOI: 10.24963/ijcai.2024/743

SMLE: Safe Machine Learning via Embedded Overapproximation

Auteurs: Matteo Francobaldi, Michele Lombardi
Publié dans: Proceedings of the AAAI Conference on Artificial Intelligence, Numéro 39, 2025, ISSN 2374-3468
Éditeur: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I26.34938

Understanding the Impact of Value Selection Heuristics in Scheduling Problems

Auteurs: Tim Luchterhand, Emmanuel Hebrard, Sylvie Thiébaux.
Publié dans: Proceedings of the 1st International Conference on Principles and Practice of Constraint Programming (CP-25), 2025
Éditeur: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
DOI: 10.4230/LIPICS.CP.2025.27

Towards Feasible Higher-Dimensional Potential Heuristics

Auteurs: Daniel Fiser, Marcel Steinmetz
Publié dans: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Éditeur: AAAI Press

Iterative Oversubscription Planning with Goal-Conflict Explanations: Scaling Up Through Policy-Guidance Approximation

Auteurs: Rebecca Eiflera, Daniel Fišer, Aleena Siji, Jörg Hoffmann
Publié dans: Proceedings of the 27th European Conference on Artificial Intelligence (ECAI'24), 2024
Éditeur: IOS Press

Effective Data Generation and Feature Selection in Learning for Planning

Auteurs: Mingyu Hao, Dillon Z. Chen, Felipe Trevizan, Sylvie Thiebaux
Publié dans: Proceedings of the 28th European Conference on Artificial Intelligence, 2025
Éditeur: IOS Press

Safety Verification of Tree-Ensemble Policies via Predicate Abstraction

Auteurs: Chaahat Jain, Lorenzo Cascioli, Laurens Devos, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jörg Hoffmann
Publié dans: Proceedings of the 27th European Conference on Artificial Intelligence (ECAI'24), 2024
Éditeur: IOS Press

Automatic Metamorphic Test Oracles for Action-Policy Testing

Auteurs: Jan Eisenhut, Álvaro Torralba, Maria Christakis, Jörg Hoffmann
Publié dans: Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS'23), 2023
Éditeur: AAAI Press
DOI: 10.1609/ICAPS.V33I1.27185

Learning Efficiency Meets Symmetry Breaking

Auteurs: Yingbin Bai, Sylvie Thiébaux, Felipe Trevizan
Publié dans: Proceedings of the 35th International Conference on Automated Planning and Scheduling, 2025
Éditeur: AAAI Press

Learning Precedences for Scheduling Problems with Graph Neural Networks

Auteurs: Hélène Verhaeghe, Quentin Cappart, Gilles Pesant, Claude-Guy Quimper
Publié dans: 30th International Conference on Principles and Practice of Constraint Programming (CP 2024), 2024
Éditeur: Leibniz International Proceedings in Informatics (LIPIcs)
DOI: 10.4230/LIPICS.CP.2024.30

Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning

Auteurs: Dillon Z. Chen, Sylvie Thiébaux
Publié dans: Proceedings of the 17th International Symposium on Combinatorial Search (SOCS'24), 2024
Éditeur: AAAI Press
DOI: 10.48550/arXiv.2404.05235

Complexity of Weighted First-Order Model Counting in the Two-Variable Fragment with Counting Quantifiers: A Bound to Beat

Auteurs: Jan Tóth, Ondřej Kuželka
Publié dans: Proceedings of the TwentyFirst International Conference on Principles of Knowledge Representation and Reasoning, 2024, ISSN 2334-1033
Éditeur: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/KR.2024/64

Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning

Auteurs: Dillon Z. Chen, Felipe Trevizan, Sylvie Thiébaux
Publié dans: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Éditeur: AAAI Press
DOI: 10.1609/icaps.v34i1.31462

Assessing the Transparency and Explainability of AI Algorithms in Planning and Scheduling Tools: A Review of the Literature

Auteurs: Sofia Morandini, Federico Fraboni, Enzo Balatti, Aranka Hackmann, Hannah Brendel, Gabriele Puzzo, Lucia Volpi, Davide Giusino, Marco De Angelis, Luca Pietrantoni.
Publié dans: Proceedings of the 14th International Conference on Applied Human Factors and Ergonomics (AHFE'23), 2023
Éditeur: AHFE International
DOI: 10.54941/ahfe1004068

Decision-Focused Learning to Predict Action Costs for Planning

Auteurs: Jayanta Mandi, Marco Foschini, Daniel Höller, Sylvie Thiébaux, Jörg Hoffmann, Tias Guns
Publié dans: Proceedings of the 27th European Conference on Artificial Intelligence (ECAI'24), 2024
Éditeur: IOS Press

Explainability Insights to Cellular Simultaneous Recurrent Neural Networks for Classical Planning

Auteurs: Michaela Urbanovská, Antonín Komenda
Publié dans: Proceedings of the 16th International Conference on Agents and Artificial Intelligence (ICAART'24), Numéro Volume 3, 2024, ISSN 2184-433X
Éditeur: SciTePress
DOI: 10.5220/0012375800003636

State Encodings for GNN-Based Lifted Planners

Auteurs: Rostislav Horčik, Gustav Šír, Vítězslav Šimek, Tomáš Pevný
Publié dans: Proceedings of the AAAI Conference on Artificial Intelligence, Numéro 39, 2025, ISSN 2374-3468
Éditeur: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I25.34853

Score Function Gradient Estimation to Widen the Applicability of Decision-Focused Learning

Auteurs: Mattia Silvestri, Senne Berden, Jayanta Mandi, Ali Mahmutogullari, Maxime Mulamba, Allegra De Filippo, Tias Guns, Michele Lombardi
Publié dans: Proceedings of the ICML Workshop Differentiable Almost Everything workshop, 2023
DOI: 10.48550/arXiv.2307.05213

Robustness Verification of Multi-Class Tree Ensembles

Auteurs: Laurens Devos, Lorenzo Cascioli, Jesse Davis
Publié dans: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024, ISSN 2159-5399
Éditeur: AAAI Press, Washington, DC, USA
DOI: 10.1609/aaai.v38i19.30093

Learning Generalised Policies for Numeric Planning

Auteurs: Ryan Xiao Wang, Sylvie Thiébaux
Publié dans: Proceedings of the 34th International Conference on Automated Planning and Scheduling (CAPS'24), 2024
Éditeur: AAAI Press

Expressiveness of Graph Neural Networks in Planning Domains

Auteurs: Rostislav Horcik, Gustav Sir
Publié dans: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Éditeur: AAAI Press

On the Computational Complexity of Stackelberg Planning and Meta-Operator Verification

Auteurs: Gregor Behnke; Marcel Steinmetz
Publié dans: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Éditeur: AAAI Press

Action Policy Explanations in Oversubscription Planning

Auteurs: Aleena Siji, Rebecca Eifler, Daniel Fišer, Jörg Hoffmann
Publié dans: Proceedings of the ICAPS Workshop on Human-Aware and Explainable Planning (HAXP'23), 2023
Éditeur: none

Fast and Robust Resource-Constrained Scheduling with Graph Neural Networks

Auteurs: Florent Teichteil-Koenigsbuch, Guillaume Poveda, Guillermo Gonzales de Garibay Barba, Tim Luchterhand, Sylvie Thiébaux
Publié dans: Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS'23), 2023
Éditeur: AAAI
DOI: 10.1609/icaps.v33i1.27244

Formal Explanations of Neural Network Policies for Planning

Auteurs: Renee Selvey, Alban Grastien, Sylvie Thiébaux
Publié dans: Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), 2023
Éditeur: IJCAI.org
DOI: 10.24963/ijcai.2023/605

A Deep Learning Blueprint for Relational Databases

Auteurs: Lukáš Zahradník, Jan Neumann, Gustav Šír
Publié dans: Proceedings of the NeurIPS Workshop on Table Representation Learning (TRL'23), 2023
Éditeur: none

Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities

Auteurs: Jayanta Mandi, James Kotary, Senne Berden, Maxime Mulamba, Victor Bucarey, Tias Guns, Ferdinando Fioretto
Publié dans: Journal of Artificial Intelligence Research, Numéro 80, 2024, ISSN 1076-9757
Éditeur: AI Access Foundation
DOI: 10.1613/jair.1.15320

Machine Learning

Auteurs: Davis, Jesse; Bransen, Lotte; Devos, Laurens; Jaspers, Arne; Meert, Wannes; Robberechts, Pieter; Van Haaren, Jan; Van Roy, Maaike
Publié dans: Machine Learning, 2024, ISSN 0885-6125
Éditeur: Springer Verlag
DOI: 10.1007/s10994-024-06585-0

User perspectives on AI explainability in aerospace manufacturing: a Card-Sorting study

Auteurs: Morandini, Sofia; Fraboni, Federico; Hall, Mark; Quintana-Amate, Santiago; Pietrantoni, Luca
Publié dans: Frontiers in Organizational Psychology, 2025, ISSN 2813-771X
Éditeur: Frontiers
DOI: 10.3389/FORGP.2025.1538438

Knowledge-Based Systems

Auteurs: Mattia Silvestri; Allegra De Filippo; Michele Lombardi; Michela Milano
Publié dans: Knowledge-Based Systems, 2024, ISSN 0950-7051
Éditeur: Elsevier
DOI: 10.1016/J.KNOSYS.2024.112383

The TOAD System for Totally Ordered HTN Planning

Auteurs: Daniel Höller
Publié dans: Journal of Artificial Intelligence Research, Numéro 80, 2024, ISSN 1076-9757
Éditeur: AI Access Foundation
DOI: 10.1613/JAIR.1.14945

Cognition, Technology and Work

Auteurs: Morandini, Sofia; Fraboni, Federico; Hall, Mark; Quintana-Amate, Santiago; Pietrantoni, Luca
Publié dans: Cognition, Technology & Work, 2024, ISSN 1435-5558
Éditeur: Springer Nature
DOI: 10.1007/S10111-024-00785-3

A Markov Framework for Learning and Reasoning About Strategies in Professional Soccer

Auteurs: Maaike Van Roy, Peter Robberechts, Wen Chi Yang, Luc De Raedt, Jesse Davis
Publié dans: Journal Of Artificial Intelligence Research, Numéro 77, 2023, ISSN 1076-9757
Éditeur: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.1.13934

Complexity of minimum-size arc-inconsistency explanations

Auteurs: Bessiere, Christian; Carbonnel, Clément; Cooper, Martin C.; Hebrard, Emmanuel
Publié dans: Constraints, 2023, ISSN 1572-9354
Éditeur: Springer
DOI: 10.1007/S10601-023-09360-5

Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned

Auteurs: Davis, Jesse; Bransen, Lotte; Devos, Laurens; Jaspers, Arne; Meert, Wannes; Robberechts, Pieter; Van Haaren, Jan; Van Roy, Maaike
Publié dans: Machine Learning, 2024, ISSN 1573-0565
Éditeur: Springer
DOI: 10.1007/S10994-024-06585-0

A rolling horizon heuristic approach for a multi-stage stochastic waste collection problem

Auteurs: Andrea Spinelli, Francesca Maggioni, Tânia Rodrigues Pereira Ramos, Ana Paula Barbosa-Póvoa, Daniele Vigo
Publié dans: European Journal of Operational Research, Numéro 323, 2025, ISSN 0377-2217
Éditeur: Elsevier BV
DOI: 10.1016/J.EJOR.2024.11.041

An efficient heuristic for very large-scale vehicle routing problems with simultaneous pickup and delivery

Auteurs: Francesco Cavaliere, Luca Accorsi, Demetrio Laganà, Roberto Musmanno, Daniele Vigo
Publié dans: Transportation Research Part E: Logistics and Transportation Review, Numéro Volume 186, June 2024, 2024, ISSN 1878-5794
Éditeur: Elsevier
DOI: 10.1016/j.tre.2024.103550

Trustworthiness of AI in Planning and Scheduling: The Experience of the TUPLES Project

Auteurs: Angelo Gordini, Matteo Pozzi, Michele Lombardi, Thomas Sergeys, Tias Guns, Andrea De Cesarei, Sofia Morandini, Sylvie Thiébaux
Publié dans: Lecture Notes in Computer Science, Decision Sciences, 2025
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78241-1_30

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