IEEE PDCO 2027

Introduction

The IEEE Workshop PDCO 2027, Seattle, USA, will be the 17th edition of the IEEE Workshop on Parallel / Distributed Combinatorics and Optimization that will be held in conjunction with the 41st IEEE International Parallel and Distributed Processing Symposium (IPDPS).
The PDCO Workshop comes from the merging of the successful Parallel Computing and Optimization (PCO) workshop and Nature Inspired Distributed Computing (NIDISC) workshop in 2017. Both workshops were continuously held in conjunction with IPDPS.

The first edition of workshop PCO was held in Anchorage USA 2011. PCO was held in Shanghai China 2012, Boston USA 2013, Phoenix USA 2014, Hyderabad India 2015, Chicago USA 2016. After the merging with NIDISC, the workshop name was Parallel and Distributed Computing and Optimization (PDCO). It was held in conjunction with IPDPS Orlando USA in 2017. Then it was held in Vancouver, Canada in 2018. In 2019, workshop PDCO became IEEE Workshop on Parallel / Distributed Combinatorics and Optimization (IEEE PDCO 2019) and was held in conjunction with IPDPS Rio de Janeiro, Brazil. Then the workshop was held in New Orleans, Louisiana USA 2020 (virtual), Portland Oregon 2021 (remotely), Lyon France 2022 (remotely) St. Petersburg Florida USA 2023, San Francisco, USA 2024, Milan, Italy 2025 and New Orleans, USA, 2026.

The series of Workshops has been very successful in the past years with many attendees (in average 20 attendees) and prestigious keynote speakers such as Professors Laurence T. Yang (St Francis Xavier University), Dimitri Bertsekas (MIT), Alex Pothen (Purdue University), Keqin Li (State University of New York), Frédéric Vivien (Ecole Normale Supérieure de Lyon), Anne Benoit (Ecole Normale Supérieure de Lyon), Georges Da Costa (Université de Toulouse) and Cynthia Phillips (Sandia National Laboratory).

Scope

The IEEE Workshop on Parallel / Distributed Combinatorics and Optimization aims at providing a forum for scientific researchers and engineers on recent advances in the field of parallel or distributed computing for difficult combinatorial optimization problems, like 0-1 multidimensional knapsack problems, cutting stock problems, scheduling problems, large scale linear programming problems, nonlinear optimization problems and global optimization problems. Emphasis is placed on new techniques for the solution of these difficult problems like cooperative methods for integer programming problems. Techniques based on metaheuristics and nature-inspired paradigms are considered. Aspects related to Combinatorial Scientific Computing (CSC) are also considered. In particular, we solicit submissions of original manuscripts on sparse matrix computations, graph algorithms and original parallel or distributed algorithms. The use of new approaches in High Performance Computing like GPU, MIC, FPGA, volunteer computing, P2P computing as well as quantum computing is taken into consideration. Application to cloud computing, planning, logistics, manufacturing, finance, telecommunications and computational biology are considered.

Topics

• Integer programming, linear programming, nonlinear programming.

• Exact methods, heuristics.

• Parallel algorithms for combinatorial optimization.

• Parallel metaheuristics.

• Parallel and distributed metaheuristics for optimization (algorithms, technologies and tools).

• Parallel and distributed computational intelligence methods (e.g. evolutionary algorithms, swarm intelligence, ant colonies, cellular automata, DNA and molecular computing for problem solving environments.

• Applications combining traditional parallel and distributed computing and optimization techniques as well as theoretical issues (convergence, complexity).

• Distributed optimization algorithms.

• Parallel sparse matrix computations, graph algorithms, load balancing.

• Hybrid computing and the solution of optimization problems.

• Peer-to-peer computing and optimization problems.

• Quantum optimization.

• Applications: cloud computing, planning, logistics, manufacturing, finance, telecommunications, computational biology, combinatorial algorithms in high performance computing.
  
  

Previous editions:

PCO 2011          PDCO 2017          PDCO 2023

PCO 2012          PDCO 2018          PDCO 2024

PCO 2013          PDCO 2019          PDCO 2025

PCO 2014          PDCO 2020           PDCO 2026

PCO 2015          PDCO 2021

PCO 2016          PDCO 2022