Professor Peter Stuckey

  • Room: Level: 06 Room: 6.19
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Combinatorial Optimization
  • Constraint Programming
  • Declarative Languages

Personal webpage

http://people.eng.unimelb.edu.au/pstuckey

Biography

Peter Stuckey is an Adjunct Professor in the School of Computing and Information Systems at The University of Melbourne and a Professor in the Faculty of Information Technology at Monash University.

Prof Stuckey is a pioneer in constraint programming, helping to develop the semantics and one of the earliest systems. He led the G12 project, a software platform for solving large scale industrial combinatorial optimisation problems. The system uses Constraint Programming (CP) to allow problems to be stated simply, and then solved efficiently. Both solution development time and computing time and scalability can be dramatically reduced. Advanced software engineering is used to encapsulate algorithms from several different disciplines, so they can be reused and combined freely. Program development can be accelerated by mapping low level computation back to the problem model enabling the programmer to analyse and improve algorithm behaviour. This research will enable Australian industry to exploit resources more efficiently; it will support more efficient management of complex private and public utilities such as transportation, communication, power and water; and it will support optimal and justifiable strategic decision making and investment.

Recent publications

  1. De Una, D.; Gange, G.; Schachte, P.; Stuckey, PJ. Compiling CP subproblems to MDDs and d-DNNFs. Constraints. SPRINGER. 2019, Vol. 24, Issue 1, pp. 56-93. DOI: 10.1007/s10601-018-9297-2
  2. Codish, M.; Miller, A.; Prosser, P.; Stuckey, PJ. Constraints for symmetry breaking in graph representation. Constraints. SPRINGER. 2019, Vol. 24, Issue 1, pp. 1-24. DOI: 10.1007/s10601-018-9294-5
  3. Konagurthu, AS.; Subramanian, R.; Allison, L.; Abramson, D.; De La Banda, MG.; Stuckey, PJ.; Lesk, AM. Information-Theoretic Inference of an Optimal Dictionary of Protein Supersecondary Structures.. Methods in molecular biology (Clifton, N.J.). Springer New York. 2019, Vol. 1958, pp. 123-131. DOI: 10.1007/978-1-4939-9161-7_6
  4. Mesnard, F.; Stuckey, PJ. Preface. . 2019, Vol. 11408 LNCS, pp. V-VI.
  5. Ganji, M.; Chan, J.; Stuckey, PJ.; Bailey, J.; Leckie, C.; Ramamohanarao, K.; Park, L. Semi-supervised blockmodelling with pairwise guidance. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2019, Vol. 11052 LNAI, pp. 158-174. DOI: 10.1007/978-3-030-10928-8_10
  6. Blom, M.; Pearce, AR.; Stuckey, PJ. Short-term planning for open pit mines: a review. International Journal of Mining, Reclamation and Environment. TAYLOR & FRANCIS LTD. 2019, Vol. 33, Issue 5, pp. 318-339. DOI: 10.1080/17480930.2018.1448248
  7. Kafle, B.; Gallagher, JP.; Gange, G.; Schachte, P.; Sondergaard, H.; Stuckey, PJ. An iterative approach to precondition inference using constrained Horn clauses. Theory and Practice of Logic Programming. CAMBRIDGE UNIV PRESS. 2018, Vol. 18, Issue 3-4, pp. 553-570. DOI: 10.1017/S1471068418000091
  8. Blom, M.; Stuckey, PJ.; Teague, VJ. Ballot-Polling Risk Limiting Audits for IRV Elections. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2018, Vol. 11143 LNCS, pp. 17-34. DOI: 10.1007/978-3-030-00419-4_2
  9. Codish, M.; Ehlers, T.; Gange, G.; Itzhakov, A.; Stuckey, PJ. Breaking symmetries with lex implications. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2018, Vol. 10818 LNCS, pp. 182-197. DOI: 10.1007/978-3-319-90686-7_12
  10. Blom, M.; Stuckey, PJ.; Teague, VJ. Computing the Margin of Victory in Preferential Parliamentary Elections. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2018, Vol. 11143 LNCS, pp. 1-16. DOI: 10.1007/978-3-030-00419-4_1
  11. Demirović, E.; Stuckey, PJ. Constraint programming for high school timetabling: A scheduling-based model with hot starts. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2018, Vol. 10848 LNCS, pp. 135-152. DOI: 10.1007/978-3-319-93031-2_10
  12. Artigues, C.; Hebrard, E.; Pencole, Y.; Schutt, A.; Stuckey, P. Data Instance generator and optimization models for evacuation planning in the event of wildfire. CEUR Workshop Proceedings. CEUR Workshop Proceedings. 2018, Vol. 2146, pp. 75-86.
  13. Bjordal, G.; Flener, P.; Pearson, J.; Stuckey, PJ.; Tack, G. Declarative local-search neighbourhoods in minizinc. 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE. 2018, Vol. 2018-November, pp. 98-105. DOI: 10.1109/ICTAI.2018.00025
  14. Ganji, M.; Chan, J.; Stuckey, PJ.; Bailey, J.; Leckie, C.; Ramamohanarao, K.; Davidson, I. Image constrained blockmodelling: A constraint programming approach. SIAM International Conference on Data Mining, SDM 2018. Society for Industrial and Applied Mathematics. 2018, pp. 19-27.
  15. Ganj, M.; Bailey, J.; Stuckey, PJ. Lagrangian constrained community detection. 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. AAAI. 2018, pp. 2983-2990.
  16. De Uña, D.; Rümmele, N.; Gange, G.; Schachte, P.; Stuckey, PJ. Machine learning and constraint programming for relational-to-ontology schema mapping. IJCAI International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence. 2018, Vol. 2018-July, pp. 1277-1283.
  17. Kreter, S.; Schutt, A.; Stuckey, PJ.; Zimmermann, J. Mixed-integer linear programming and constraint programming formulations for solving resource availability cost problems. European Journal of Operational Research. ELSEVIER SCIENCE BV. 2018, Vol. 266, Issue 2, pp. 472-486. DOI: 10.1016/j.ejor.2017.10.014
  18. Blom, M.; Pearce, AR.; Stuckey, PJ. Multi-objective short-term production scheduling for open-pit mines: a hierarchical decomposition-based algorithm. Engineering Optimization. TAYLOR & FRANCIS LTD. 2018, Vol. 50, Issue 12, pp. 2143-2160. DOI: 10.1080/0305215X.2018.1429601
  19. Zarate, DC.; Le Bodic, P.; Dwyer, T.; Gange, G.; Stuckey, P. Optimal Sankey Diagrams via Integer Programming. 2018 IEEE Pacific Visualization Symposium (PacificVis). IEEE. 2018, Vol. 2018-April, pp. 135-139. DOI: 10.1109/PacificVis.2018.00025
  20. Amadini, R.; Gange, G.; Stuckey, PJ. Propagating lex, find and replace with dashed strings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2018, Vol. 10848 LNCS, pp. 18-34. DOI: 10.1007/978-3-319-93031-2_2

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile