Parallel MO-PBIL: Computing pareto optimal frontiers efficiently with applications in reinsurance analytics-Reference-Cited by-同舟云学术

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Parallel MO-PBIL: Computing pareto optimal frontiers efficiently with applications in reinsurance analytics

Published:2014-07 Issue: Volume: Page:
ISSN:
Container-title:2014 International Conference on High Performance Computing & Simulation (HPCS)
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Author:

Brown Leah,Beria Anirudha Ashok,Cortes Omar A. C.,Rau-Chaplin Andrew,Wilson Duane,Burke Neil,Gaiser-Porter Jurgen

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/6895221/6903651/06903766.pdf?arnumber=6903766

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An evolutionary strategy for multiobjective reinsurance optimization;Journal of the Operational Research Society;2017-12-17

2. Enhanced multiobjective population-based incremental learning with applications in risk treaty optimization;Evolutionary Intelligence;2016-10-24

3. Enhanced Multiobjective Population-Based Incremental Learning with Applications in Risk Treaty Optimization;Applications of Evolutionary Computation;2016

4. Dynamic optimization of multi-layered reinsurance treaties;Proceedings of the 30th Annual ACM Symposium on Applied Computing;2015-04-13

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