Abstract
Parallel Genetic Algorithm (PGA) is employed to solve inverse problems. The PGA is codified considering the island model (individuals are free to migrate to any other processor, subjected to specific rules); and stepping-stone model (migration is allowed only for the closest processors). The parallel code is generated using calls to the message passing communication library MPI (Message Passing Interface). In our GA approach, a new genetic operator, named epidemic is applied. This technique is employed to solve an inverse heat conduction problem. The goal is to determine the initial temperature from the transient noisy temperature profile at a given time. This ill-posed problem requires the use of a regularization technique.
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The authors would like to thank the FAPESP and CNPq, Brazilian agencies for research support.
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Sambatti, S.B.M., de Campos Velho, H.F., Chiwiacowsky, L.D. (2019). Epidemic Genetic Algorithm for Solving Inverse Problems: Parallel Algorithms. In: Constanda, C., Harris, P. (eds) Integral Methods in Science and Engineering. Birkhäuser, Cham. https://doi.org/10.1007/978-3-030-16077-7_30
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DOI: https://doi.org/10.1007/978-3-030-16077-7_30
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