PDCO 2019 - 9th IEEE Workshop Parallel / Distributed Combinatorics and Optimization (PDCO 2019)

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 considered. In particular, we solicit submissions of original manuscripts on sparse matrix computations, graph algorithm and original parallel or distributed algorithms. The use of new approaches in parallel and distributed computing like GPU, MIC, FPGA, volunteer computing are considered. 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 computational intelligence methods (e.g. evolutionary algorithms, swarm intelligence, ant colonies, cellular automata, DNA and molecular computing) for problem solving environments.
Parallel and distributed metaheuristics for optimization (algorithms, technologies and tools).
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.
Applications: cloud computing, planning, logistics, manufacturing, finance, telecommunications,