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Tuning a hybrid SA based algorithm applied to Optimal Sensor Network Design
DOI:
https://doi.org/10.24215/16666038.20.e03Keywords:
Cooling Schedule, Optimization, Sensor networks, Simulated AnnealingAbstract
Sensor network design problem (SNDP) in process plants includes the determination of which process variables should be measured to achieve a required degree of knowledge about the plant. We propose to solve the SNDP problem in plants of increasing size and complexity using a hybrid algorithm based on Simulated Annealing (HSA) as main metaheuristic and Tabu Search embedded with Strategic Oscillation (SOTS) as a subordinate metaheuristic. We are researching on the adjustments of its control parameters to obtain the best HSA performance. Experimental results indicate that a high-quality solution in reasonable computational times can be found by HSA effectively. Moreover, HSA shows good features solving SNDP compared with proposals from the literature.
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References
M. Bagajewicz, “Design and retrofit of sensor net-works in process plants,”AIChE Journal, vol. 43, no. 9,pp. 2300–2306, 1997.
D. Nguyen and M. Bagajewicz, “New efficient breadth-first/level traversal tree search method for the designand upgrade of sensor networks,”AIChE Journal,vol. 57, no. 5, pp. 1302–1309, 2011.
C. Gerkens and G. Heyen, “Use of parallel computersin rational design of redundant sensor networks,”Com-puters and Chemical Engineering, vol. 29, no. 6 SPEC.ISS., pp. 1379–1387, 2005.
Y.-J. He and Z.-F. Ma, “Optimal design of linear sen-sor networks for process plants: A multi-objectiveant colony optimization approach,”Chemometrics andIntelligent Laboratory Systems, vol. 135, pp. 37–47,2014.
M. Carnero, J. L. Hern ́andez, and M. S ́anchez, “Opti-mal sensor location in chemical plants using the estima-tion of distribution algorithms,”Industrial & Engineer-ing Chemistry Research, vol. 57, no. 36, pp. 12149–12164, 2018.
S. Kirkpatrick, C. G. Jr, and M. Vecchi, “Optimizationby simulated annealing,”Science, no. 220, pp. 671–680, 1983.
E. Talbi,Metaheuristics: From Design to Implementa-tion. Wiley Publishing, 2009.
J. Hernandez, C. Salto, G. Minetti, M. Carnero,C. Bermudez, and M. Sanchez, “Optimal instrumenta-tion: Adjustment and hybridization of a simulated an-nealing based technique,” inXXV Congreso Argentinode Ciencias de la Computaci ́on (CACIC 2019), pp. –,Oct. 2019.
M. Bagajewicz and M. S ́anchez, “Reallocation and up-grade of instrumentation in process plants,”ComputersChemical Engineering, vol. 24, no. 8, pp. 1945 – 1959,2000.[10]M. Bagajewicz and M. S ́anchez, “Design and upgradeof nonredundant and redundant linear sensor networks,”AIChE Journal, vol. 45, no. 9, pp. 1927–1938, 1999.
J. Romagnoli and M. Sanchez,Data Processing andReconciliation for Chemical Process Operations. Aca-demic Press: San Diego, CA, 2000.
S. Narasimhan and C. Jordache,Data Reconciliationand Gross Error Detection. Gulf Publishing Company:Houston, TX, 2000.
B. Hajek, “Cooling schedules for optimal annealing,”Mathematics of Operations Research, vol. 13, no. 2,pp. 311–329, 1988.
S. Geman and D. Geman, “Stochastic relaxation, gibbsdistributions, and the bayesian restoration of images,”IEEE Trans. Pattern Anal. Mach. Intell., vol. 6, pp. 721–741, Nov. 1984.
C. Bermudez, C. Salto, and G. Minetti, “Solving themulti-period water distribution network design prob-lem with a hybrid simulated anealling,” inComputerScience – CACIC 2018(P. Pesado and C. Aciti, eds.),(Cham), pp. 3–16, Springer International Publishing,2019.
M. F. Cardoso, R. L. Salcedo, and S. F. de Azevedo,“Nonequilibrium simulated annealing: A faster ap-proach to combinatorial minimization,”Ind. Eng.Chem. Res, vol. 33, pp. 1908–1918, 1994.
M. Ali, A. T ̈orn, and S. Viitanen, “A direct searchvariant of the simulated annealing algorithm for opti-mization involving continuous variables,”Computers& Operations Research, vol. 29, no. 1, pp. 87 – 102,2002.
J. Hernandez, C. Salto, G. Minetti, M. Carnero, andM. C. Sanchez, “Hybrid simulated annealing for opti-mal cost instrumentation in chemical plants,”ChemicalEngineering Transactions, vol. 74, pp. 709–714, May2019.
K.-L. Du and M. N. S. Swamy,Search and Optimiza-tion by Metaheuristics: Techniques and AlgorithmsInspired by Nature. Birkh ̈auser Basel, 1st ed., 2016.
M. Carnero, J. Hern ́andez, and M. S ́anchez, “A newmetaheuristic based approach for the design of sensornetworks,”Computers Chemical Engineering, vol. 55,pp. 83 – 96, 2013.
M. Bhushan and R. Rengaswamy, “Design of sensornetwork based on the signed directed graph of the pro-cess for efficient fault diagnosis,”Industrial & Engi-neering Chemistry Research, vol. 39, no. 4, pp. 999–1019, 2000.
H. Smith and N. Ichiyen, “Computer adjustment ofmetallurgical balances,”Computer Applications andProcess Control. (CIM) Bulletin, vol. 66, pp. 97–100,1973.
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Published
2020-05-26
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[1]
“Tuning a hybrid SA based algorithm applied to Optimal Sensor Network Design”, JCS&T, vol. 20, no. 1, p. e03, May 2020, doi: 10.24215/16666038.20.e03.
