CPAIOR 2017, Call for Papers

Padova, June 5-8 2017

[Apologies for cross-posting]

General Information

The Fourteenth International Conference on Integration of Artificial 
Intelligence and Operations Research Techniques in Constraint Programming will 
be held in Padova, Italy, June 5 - 8, 2017, with a Master Class on 
"Computational Techniques for Combinatorial Optimization" on June 5, and the 
Main Conference on June 6 - 8, 2017.

The aim of the conference is to bring together interested researchers from 
Constraint Programming (CP), Artificial Intelligence (AI), and Operations 
Research (OR) to present new techniques or applications in combinatorial 
optimization and to provide an opportunity for researchers in one area to learn 
about techniques in the others.

A main objective of this conference series is also to give these researchers 
the opportunity to show how the integration of techniques from different fields 
can lead to interesting results on large and complex problems.

Therefore papers that actively combine, integrate, or contrast approaches from 
more than one of the areas are especially solicited. High quality papers from a 
single area are also welcome, provided that they are of interest to other 
communities involved. Application papers showcasing CP/AI/OR techniques on 
novel and challenging applications or experience reports on such applications 
are strongly encouraged.

The program committee invites submissions that include but are not limited to 
the following topics:

Inference and relaxation methods: constraint propagation, cutting planes, 
global constraints, graph algorithms, dynamic programming, Lagrangian and 
convex relaxations, heuristic functions based on relaxations.
Search methods: branch and bound, intelligent backtracking, incomplete search, 
randomized search, portfolios, column generation, Benders decomposition or any 
other decomposition methods, local search and meta­heuristics
Integration of machine learning and optimization: learning-based search and 
heuristics, use of predictive models in optimization, constraint acquisition, 
optimization for training machine learning models
Integration methods: solver communication, model transformations and solver 
selection, parallel and distributed resolution techniques, models, and solvers.
Modeling methods: comparison of models, symmetry breaking, uncertainty, 
dominance relationships.
Innovative Applications of CP/AI/OR techniques.
Implementation of CP/AI/OR techniques and optimization systems. 

More information is available on the conference web site: 

Important Dates

Abstract submission deadline: 14 Nov
Paper submission deadline: 21 Nov
Rebuttal period: 20-23 Dec
Final notification: 16 Jan
Camera-ready version: 31 Jan

Submission process and formats

Paper submissions are of two types:

Long papers (15 pages, plus references)
Short papers (8 pages, plus references)

The conference proceedings will be published on the LNCS series.

Additionally, outstanding submissions to the technical program will be offered 
the opportunity to be published exclusively through a "fast track" process in 
the "Constraint" Journal. Journal fast track paper will still be regularly 
presented at the conference.

All papers are to be submitted electronically in PDF format via easychair:


Authors should follow the submission instructions on the conference website. In 
the particular, they should comply with the required format (LNCS style) and 
page limits.

For any queries on the submission process, please contact the program chairs at 
domin...@gmail.com and michele.lombar...@unibo.it


Program chairs:
 Domenico Salvagnin (DEI, University of Padova), 
Michele Lombardi (DISI, University of Bologna), 
Conference chair:
Domenico Salvagnin (DEI, University of Padova), 
Program Committee:
Chris Beck, University of Toronto
David Bergman, University of Connecticut
Timo Berthold, Fair Isaac Germany GmbH
Hadrien Cambazard, Grenoble INP
Andre A. Cire, University of Toronto
Matteo Fischetti, University of Padova
Bernard Gendron, Université de Montréal
Ambros Gleixner, Zuse Institute Berlin
Carla Gomes, Cornell University
Tias Guns, KU Leuven
John Hooker, Tepper School of Business, Carnegie Mellon University
Matti Järvisalo, University of Helsinki
Serdar Kadioglu, Oracle Corporation
Philip Kilby, Australia National University
Joris Kinable, Carnegie Mellon University
Jeff Linderoth, University of Wisconsin-Madison
Andrea Lodi, École Polytechnique de Montréal
Ines Lynce, Instituto Superior Técnico, Lisboa
Laurent Michel, University of Connecticut
Michela Milano, University of Bologna
Michele Monaci, University of Bologna
Siegfried Nijssen, UC Louvain
Barry O'Sullivan, University College Cork, Insight center
Claude-Guy Quimper, Université Laval
Jean-Charles Régin, Université de Nice-Sophia Antipolis
Louis-Martin Rousseau, École Polytechnique de Montréal
Ashish Sabharwal, Allen Institute for Artificial Intelligence
Scott Sanner, University of Toronto
Pierre Schaus, UC Louvain
Christian Schulte, KTH Royal Institute of Technology
Helmut Simonis, University College Cork
Christine Solnon, INSA Lyon
Peter-J. Stuckey, University of Melbourne
Michael Trick, Carnegie Mellon University
Pascal Van-Hentenryck, University of Michigan
Willem-Jan Van-Hoeve, Tepper School of Business, Carnegie Mellon University
Sicco Verwer, Delft University of Technology
Toby Walsh, University of New South Wales and Data61
Alessandro Zanarini, ABB CRC
Yingqian Zhang, TU Eindoven

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