Parallel genetic programming and its application to trading model induction

Article Article scientifique Article Parallel genetic programming and its application to trading model induction eng 1997 author Oussaidene Mouloud 88374 author Chopard Bastien 22320 author Pictet Olivier Victor Henri 63273 author Tomassini Marco 122932 1183-1198 10.1016/S0167-8191(97)00045-8 0167-8191 https://linkinghub.elsevier.com/retrieve/pii/S0167819197000458 This paper presents a scalable parallel implementation of genetic programming on distributed memory machines. The system runs multiple master-slave instances each mapped on all the allocated nodes and multithreading is used to overlap message latencies with useful computation. Load balancing is achieved using a dynamic scheduling algorithm and comparison with a static algorithm is reported. To alleviate premature convergence, asynchronous migration of individuals is performed among processes. We show that nearly linear speedups can be obtained for problems of large enough size. The system has been applied to infer robust trading strategies which is a compute-intensive financial application. Parallel genetic programming Performance analysis Financial trading models Dewey 025.063 13 Centre universitaire d'informatique 0D3 32 Département d'informatique 18 false 728 Scientific and Parallel Computing Parallel Computing 23 8 b826e661-7ae3-44c0-a51f-68e77c6cc219 Article (Published version) Restricted 1997Oussaidene_parallel_genetic_progr.pdf 1107473 application/pdf restrictedAccess Centres et instituts / Centre universitaire d'informatique Faculté des sciences / Département d'informatique

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Pictet, Olivier Victor Henri