Parallel Search and Optimisation

Joint Workshop of CP 2017, ICLP 2017 and SAT 2017

Melbourne, Australia, August 28th, 2017

(immediately following IJCAI 2017 )

Important Dates

Paper submission: June 14, 2017

Notification: July 7, 2017

PaSeO is the fifth workshop of a series started with the CP 2011 "Workshop on Parallel Methods for Constraint Solving" (Perugia, Italy), the 2012 Shonan Meeting on "Parallel Methods for Constraint Solving and Combinatorial Optimization" (Shonan Village, Japan), the CPAIOR 2013 workshop on "Parallel Methods for Combinatorial Search & Optimization" (New York, USA), and the ParSearchOpt14 workshop et the Vienna Summer of Logic (Austria).

It will be held in the spirit of the Dagstuhl Seminars (in Germany) or Shonan Meetings (in Japan), that is, a day of brainstorming and open discussion about common scientific topics, bringing researchers from various backgrounds and aiming at maximal interaction between participants, rather than a sequence of sharply focused talks with little interaction with the audience.

Aims and Scope

Over the last decade, with the development of multi-core workstations, the availability of hybrid GPGPU-enhanced systems and the increasingly generalized access to Grid and Cloud platforms as well as supercomputers worldwide, Parallel Programming has met with the mainstream. It appears as a key concern in order to use in an efficient manner the computing power at hand.

Search methods and combinatorial optimization techniques are not isolated from this phenomenon, as bigger computing power means the ability to attack more complex combinatorial problems. In the last years many experiments have been done to parallelize the execution of search methods such as SAT solving, Constraint Programming and combinatorial optimization methods such as Local Search, Meta-heuristics and Branch & Bound. However most these works have mostly been done for shared memory multi-core systems (i.e. with a few cores or tens of cores) or for small PC clusters (a few machines or tens of machines). The next challenge is to devise efficient techniques and algorithms for massively parallel computers with tens or hundreds of thousands of cores in the form of heterogeneous hybrid systems based on both multi-core processors and GPU. With the move to Exascale computing probably by the end of this decade, this trend will continue to gain importance.

An important aspect for researchers working on parallel search and optimization in different fields is to share their experience on both theoretical and practical issues. This workshop is thus aimed to be a forum for researchers willing to exchange ideas, theoretical frameworks, design of algorithms and methods, implementation issues, experimental results and to further boost this growing area of research through cross-fertilization.

Workshop Topics and Paper Submission

We would like to provide a cross-community forum for researchers working on search methods (Constraint Solving, Logic Programming, SAT solving, Artificial Intelligence, etc), combinatorial optimization methods (metaheuristics, local search, tabu search, evolutionary algorithms, ant colony optimization, particle swarm optimization, memetic algorithms, and other types of algorithms) and High Performance Computing (Grids, large PC clusters, massively parallel computers, GPGPUs) in order to tackle the challenge of efficient implementations of search and optimization methods on all kinds of parallel hardware: multi-core, GPU-based or heterogeneous massively parallel systems.

We thus solicit papers on the above topics, including reports on work in progress, as well as position papers.

Papers must be between 5 to 15 pages plus references and use the Springer LNCS style and should be submitted through EasyChair at


Philippe Codognet, University Pierre & Marie Curie, Paris, France (Chair)

Salvador Abreu, University of Evora, Portugal

Daniel Diaz, University of Paris-1, France

Program Committee

Salvador Abreu, University of Evora, Portugal

Alejandro Arbelaez (Cork Institute of Technology, Ireland)

Philippe Codognet, University Pierre & Marie Curie, Paris, France

Daniel Diaz, University of Paris-1, France

Youssef Hamadi (Ecole Plytechnique, France)

Arnaud Lalouet (Huawei Technologies, France)

Ines Lynce (University of Lisbon, INESC-ID/IST, Portugal)

Enrico Pontelli (New Mexico State University, USA)

Lakhdar Sais (Université d'Artois / CRIL, France)

Vijay Saraswat (IBM Research, USA)

Christian Schulte (KTH Royal Institute of Technology, Sweden)