Competitive Coevolution in Problem Design and Metaheuristical Parameter Tuning
The Marine Research Institute of Iceland has over the last 20 years developed and used the program gadget for modeling of the marine ecosystem around Iceland. The estimation of parameters in this program requires constrained optimization in a continuous domain. In this thesis a coevolutionary algori...
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ftskemman:oai:skemman.is:1946/18534 2023-05-15T16:47:10+02:00 Competitive Coevolution in Problem Design and Metaheuristical Parameter Tuning Guðmundur Einarsson 1988- Háskóli Íslands 2014-05 application/pdf http://hdl.handle.net/1946/18534 en eng http://hdl.handle.net/1946/18534 Stærðfræði Thesis Master's 2014 ftskemman 2022-12-11T06:57:35Z The Marine Research Institute of Iceland has over the last 20 years developed and used the program gadget for modeling of the marine ecosystem around Iceland. The estimation of parameters in this program requires constrained optimization in a continuous domain. In this thesis a coevolutionary algorithm approach is developed to tune the optimization parameters in gadget. The objective of the coevolutionary algorithm is to find optimization parameters that both make the optimization methods in gadget more robust against poorly chosen starting values and tries to reduce the computation time while maintaining convergence. This may also ease the tuning of optimization parameters for new users and may reveal other local optima in the likelihood, which may give hint of model misspecification. The algorithm is tested on functions that have similar characteristics as the log-likelihood functions in gadget and some results shown for the case of modeling haddock. Hafrannsóknarstofnun Thesis Iceland Skemman (Iceland) |
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Stærðfræði Guðmundur Einarsson 1988- Competitive Coevolution in Problem Design and Metaheuristical Parameter Tuning |
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The Marine Research Institute of Iceland has over the last 20 years developed and used the program gadget for modeling of the marine ecosystem around Iceland. The estimation of parameters in this program requires constrained optimization in a continuous domain. In this thesis a coevolutionary algorithm approach is developed to tune the optimization parameters in gadget. The objective of the coevolutionary algorithm is to find optimization parameters that both make the optimization methods in gadget more robust against poorly chosen starting values and tries to reduce the computation time while maintaining convergence. This may also ease the tuning of optimization parameters for new users and may reveal other local optima in the likelihood, which may give hint of model misspecification. The algorithm is tested on functions that have similar characteristics as the log-likelihood functions in gadget and some results shown for the case of modeling haddock. Hafrannsóknarstofnun |
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Háskóli Íslands |
format |
Thesis |
author |
Guðmundur Einarsson 1988- |
author_facet |
Guðmundur Einarsson 1988- |
author_sort |
Guðmundur Einarsson 1988- |
title |
Competitive Coevolution in Problem Design and Metaheuristical Parameter Tuning |
title_short |
Competitive Coevolution in Problem Design and Metaheuristical Parameter Tuning |
title_full |
Competitive Coevolution in Problem Design and Metaheuristical Parameter Tuning |
title_fullStr |
Competitive Coevolution in Problem Design and Metaheuristical Parameter Tuning |
title_full_unstemmed |
Competitive Coevolution in Problem Design and Metaheuristical Parameter Tuning |
title_sort |
competitive coevolution in problem design and metaheuristical parameter tuning |
publishDate |
2014 |
url |
http://hdl.handle.net/1946/18534 |
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Iceland |
genre_facet |
Iceland |
op_relation |
http://hdl.handle.net/1946/18534 |
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1766037250475294720 |