Hybrid Simulated Annealing for Optimal Cost Instrumentation in Chemical Plants
Hernandez, Jose
Salto, Carolina
Minetti, Gabriela
Carnero, Mercedes
Sanchez, Mabel C.
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Hernandez J., Salto C., Minetti G., Carnero M., Sanchez M.C., 2019, Hybrid Simulated Annealing for Optimal Cost Instrumentation in Chemical Plants, Chemical Engineering Transactions, 74, 709-714.
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Process information is the foundation upon which many common tasks in chemical plants are based. To satisfy information requirements regarding its quality and availability, it is essential to locate an appropriate set of instruments or sensor network (SN) in the plant. The SN designer should decide whether to measure each process variable or not. These decisions are mathematically formulated in terms of binary variables. This results in a combinatorial optimization problem that usually involves many decision binary variables and exhibits multiple solutions locally or globally optimal.
In this work, a metaheuristic based on simulated annealing hybridized with strategic oscillation, named HSA_SOTS, is proposed to solve the tackled problem. The performance of HSA_SOTS is evaluated considering several high scale designs with increasing complexities. The results of this metaheuristic outperform the ones presented in the literature.
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