Name
Title | ||
|---|---|---|
Parallel MO-PBIL: Computing pareto optimal frontiers efficiently with applications in reinsurance analytics |
Abstract | ||
|---|---|---|
In this paper we propose MO-PBIL, a parallel multidimensional variant of the Population Based Incremental Learning (PBIL) technique that executes efficiently on both multi-core and many-core architectures. We show how MO-PBIL can be used to address an important problem in Reinsurance Risk Analytics namely the Reinsurance Contract Optimization problem. A mix of vectorization and multithreaded parallelism is used to accelerate the three main computational steps: objective function evaluation, multidimensional dominance calculations, and multidimensional clustering. Using MO-PBIL, reinsurance contract optimization problems with a 5% discretization and 7 or less contractual layers (subcontracts) can be solved in under a 1 minute on a single workstation or server. Problems with up to 15 layers, which previously took a month or more of computation to solve, can now be solved in less than 10 minutes. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/HPCSim.2014.6903766 | High Performance Computing & Simulation |
Keywords | Field | DocType |
Pareto optimisation,insurance data processing,learning (artificial intelligence),parallel algorithms,pattern clustering,risk management,Pareto optimal frontiers,many-core architecture,multi-core architecture,multidimensional clustering,multidimensional dominance calculation,multithreaded parallelism,objective function evaluation,parallel MO-PBIL technique,parallel population based incremental learning,reinsurance contract optimization problem,reinsurance risk analytics,vectorization,formatting,insert,style,styling | Mathematical optimization,Reinsurance,Parallel algorithm,Computer science,Parallel computing,Vectorization (mathematics),Linear programming,Cluster analysis,Analytics,Population-based incremental learning,Optimization problem,Distributed computing | Conference |
Citations | PageRank | References |
1 | 0.39 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leah Brown | 1 | 1 | 0.39 |
| Anirudha Ashok Beria | 2 | 1 | 0.39 |
| Omar Andrés Carmona Cortes | 3 | 8 | 2.69 |
| Andrew Rau-chaplin | 4 | 638 | 61.65 |
| Duane Wilson | 5 | 3 | 0.82 |
| Neil Burke | 6 | 3 | 1.76 |
| Jürgen Gaiser-Porter | 7 | 3 | 0.82 |
| Rau-Chaplin, A. | 8 | 47 | 4.44 |