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Documents authored by Ajwani, Deepak

Document
DOI: 10.4230/DagRep.14.10.76
Machine Learning Augmented Algorithms for Combinatorial Optimization Problems (Dagstuhl Seminar 24441)

Authors: Deepak Ajwani, Bistra Dilkina, Tias Guns, and Ulrich Carsten Meyer

Published in: Dagstuhl Reports, Volume 14, Issue 10 (2025)

Abstract
Combinatorial optimization problems are pervasive across critical domains, including business analytics, engineering, supply chain management, transportation, and bioinformatics. Many of these problems are NP-hard, posing significant challenges for even moderately sized instances. Moreover, even when polynomial-time algorithms exist, their practical implementation can be computationally expensive for real-world applications. This has driven decades of research across diverse fields, encompassing exact and approximation algorithms, parameterized algorithms, algorithm engineering, operations research, optimization solvers (such as mixed-integer linear programming and constraint programming solvers), and nature-inspired metaheuristics. Recently, there has been a surge in research exploring the synergistic integration of machine learning techniques with algorithmic insights and optimization solvers to enhance the scalability of solving combinatorial optimization problems. However, research efforts in this area are currently fragmented across several distinct communities, including those focused on "Learning to scale optimization solvers," "Algorithm Engineering," "Algorithms with predictions," and "Decision-focused learning." This seminar brought together researchers from these diverse communities, fostering a dialogue on effectively combining algorithm engineering techniques, optimization solvers, and machine learning to address these challenging problems. The seminar facilitated the development of a shared vocabulary, clarifying similarities and distinctions between concepts across different research areas. Furthermore, significant progress was made in identifying key research directions for the future advancement of this field. We anticipate that these outcomes will serve as a valuable roadmap for advancing this exciting research area.
Cite as

Deepak Ajwani, Bistra Dilkina, Tias Guns, and Ulrich Carsten Meyer. Machine Learning Augmented Algorithms for Combinatorial Optimization Problems (Dagstuhl Seminar 24441). In Dagstuhl Reports, Volume 14, Issue 10, pp. 76-100, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{ajwani_et_al:DagRep.14.10.76,
  author =	{Ajwani, Deepak and Dilkina, Bistra and Guns, Tias and Meyer, Ulrich Carsten},
  title =	{{Machine Learning Augmented Algorithms for Combinatorial Optimization Problems (Dagstuhl Seminar 24441)}},
  pages =	{76--100},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2025},
  volume =	{14},
  number =	{10},
  editor =	{Ajwani, Deepak and Dilkina, Bistra and Guns, Tias and Meyer, Ulrich Carsten},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.10.76},
  URN =		{urn:nbn:de:0030-drops-230216},
  doi =		{10.4230/DagRep.14.10.76},
  annote =	{Keywords: Algorithm Engineering, Combinatorial Optimization, Constraint Solvers, Machine Learning}
}
Document
DOI: 10.4230/DagRep.13.8.1
Recent Trends in Graph Decomposition (Dagstuhl Seminar 23331)

Authors: George Karypis, Christian Schulz, Darren Strash, Deepak Ajwani, Rob H. Bisseling, Katrin Casel, Ümit V. Çatalyürek, Cédric Chevalier, Florian Chudigiewitsch, Marcelo Fonseca Faraj, Michael Fellows, Lars Gottesbüren, Tobias Heuer, Kamer Kaya, Jakub Lacki, Johannes Langguth, Xiaoye Sherry Li, Ruben Mayer, Johannes Meintrup, Yosuke Mizutani, François Pellegrini, Fabrizio Petrini, Frances Rosamond, Ilya Safro, Sebastian Schlag, Roohani Sharma, Blair D. Sullivan, Bora Uçar, and Albert-Jan Yzelman

Published in: Dagstuhl Reports, Volume 13, Issue 8 (2024)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23331 "Recent Trends in Graph Decomposition", which took place from 13. August to 18. August, 2023. The seminar brought together 33 experts from academia and industry to discuss graph decomposition, a pivotal technique for handling massive graphs in applications such as social networks and scientific simulations. The seminar addressed the challenges posed by contemporary hardware designs, the potential of deep neural networks and reinforcement learning in developing heuristics, the unique optimization requirements of large sparse data, and the need for scalable algorithms suitable for emerging architectures. Through presentations, discussions, and collaborative sessions, the event fostered an exchange of innovative ideas, leading to the creation of community notes highlighting key open problems in the field.
Cite as

George Karypis, Christian Schulz, Darren Strash, Deepak Ajwani, Rob H. Bisseling, Katrin Casel, Ümit V. Çatalyürek, Cédric Chevalier, Florian Chudigiewitsch, Marcelo Fonseca Faraj, Michael Fellows, Lars Gottesbüren, Tobias Heuer, Kamer Kaya, Jakub Lacki, Johannes Langguth, Xiaoye Sherry Li, Ruben Mayer, Johannes Meintrup, Yosuke Mizutani, François Pellegrini, Fabrizio Petrini, Frances Rosamond, Ilya Safro, Sebastian Schlag, Roohani Sharma, Blair D. Sullivan, Bora Uçar, and Albert-Jan Yzelman. Recent Trends in Graph Decomposition (Dagstuhl Seminar 23331). In Dagstuhl Reports, Volume 13, Issue 8, pp. 1-45, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{karypis_et_al:DagRep.13.8.1,
  author =	{Karypis, George and Schulz, Christian and Strash, Darren and Ajwani, Deepak and Bisseling, Rob H. and Casel, Katrin and \c{C}ataly\"{u}rek, \"{U}mit V. and Chevalier, C\'{e}dric and Chudigiewitsch, Florian and Faraj, Marcelo Fonseca and Fellows, Michael and Gottesb\"{u}ren, Lars and Heuer, Tobias and Kaya, Kamer and Lacki, Jakub and Langguth, Johannes and Li, Xiaoye Sherry and Mayer, Ruben and Meintrup, Johannes and Mizutani, Yosuke and Pellegrini, Fran\c{c}ois and Petrini, Fabrizio and Rosamond, Frances and Safro, Ilya and Schlag, Sebastian and Sharma, Roohani and Sullivan, Blair D. and U\c{c}ar, Bora and Yzelman, Albert-Jan},
  title =	{{Recent Trends in Graph Decomposition (Dagstuhl Seminar 23331)}},
  pages =	{1--45},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2024},
  volume =	{13},
  number =	{8},
  editor =	{Karypis, George and Schulz, Christian and Strash, Darren},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.8.1},
  URN =		{urn:nbn:de:0030-drops-198114},
  doi =		{10.4230/DagRep.13.8.1},
  annote =	{Keywords: combinatorial optimization, experimental algorithmics, parallel algorithms}
}
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