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- W2900451337 abstract "The dynamic optimization is a useful mathematical tool to find the optimal solution of problems where a significant variability with the time of the present variables is observed. The solution to these problems may become difficult in some cases, such as problems with temporal constraints or changes in the solution profile over time. In such cases, both the quality of the solution and the computational cost can be improved. This work aims to develop an adaptive numerical method, based on wavelets analysis, to solve dynamic optimization problems. The method was developed in the Python programming language, using the Gekko package. Two cases of dynamic optimization were solved and the results showed that the computational cost could be significantly reduced." @default.
- W2900451337 created "2018-11-29" @default.
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- W2900451337 date "2018-12-21" @default.
- W2900451337 modified "2023-09-23" @default.
- W2900451337 title "DYNAMIC OPTIMIZATION USING ADAPTIVE GRID REFINEMENT WITH WAVELETS TRANSFORM in PYTHON" @default.
- W2900451337 hasPublicationYear "2018" @default.
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