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A Parallel Optimization Framework for Inverse Problems

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Figure

Figure 3.1 Different optimization algorithms available in the module for solving inverse problems
Figure 3.2 Flowchart of genetic algorithms (GA).
Figure 4.1 Schematic layout of parallel hybrid GA-LS-FEM optimization framework. The GA solution or the MGA alternatives are passed as initial starting guess to local search methods
Figure 4.2 Three levels of MPI communicator hierarchy with multiple groups (n) performing GA/LS operations, and each group using different number of processors in a group (Pi.pi + 1)
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