Hybrid Bat Algorithm for Parameter Identification of an E. Coli Cultivation Process Model

In this paper, a hybrid scheme using Bat Algorithm (BA) and Sequential Quadratic Programming (SQP) method is introduced. In the hybrid BA-SQP, the role of BA is to generate feasible solutions to a problem. The role of SQP is to exploit the information gathered by BA. This process obtains a solution...

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Veröffentlicht in:Biotechnology, biotechnological equipment Jg. 27; H. 6; S. 4323 - 4326
Hauptverfasser: Roeva, Olympia Nikolaeva, Fidanova, Stefka Stoyanova
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Sofia Taylor & Francis 2013
Taylor & Francis Ltd
Schlagworte:
Algorithms
Ant colony optimization
Bat Algorithm
Batch culture
Computer applications
Cultivation
cultivation process
E coli
Escherichia coli
Formicidae
local search
Mathematical models
metaheuristics
Parameter identification
Quadratic programming
Searching
SQP
ISSN:1310-2818, 1314-3530
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Abstract In this paper, a hybrid scheme using Bat Algorithm (BA) and Sequential Quadratic Programming (SQP) method is introduced. In the hybrid BA-SQP, the role of BA is to generate feasible solutions to a problem. The role of SQP is to exploit the information gathered by BA. This process obtains a solution which is at least as good as-but usually better than-the best solution devised by BA. To demonstrate the usefulness of the presented approach, the hybrid scheme was applied to parameter identification of an E. coli MC4110 fed-batch cultivation process model. A comparison with both the conventional BA and SQP method is presented. The results showed that the hybrid BA-SQP has the advantages of both BA's global search ability and SQP's local search ability, thus enhancing the overall search ability and computational efficiency. For comparison, the results obtained by applying Ant colony optimization algorithm in conditions similar to those of BA are further shown.
AbstractList In this paper, a hybrid scheme using Bat Algorithm (BA) and Sequential Quadratic Programming (SQP) method is introduced. In the hybrid BA—SQP, the role of BA is to generate feasible solutions to a problem. The role of SQP is to exploit the information gathered by BA. This process obtains a solution which is at least as good as—but usually better than—the best solution devised by BA. To demonstrate the usefulness of the presented approach, the hybrid scheme was applied to parameter identification of an E. coli MC4110 fed-batch cultivation process model. A comparison with both the conventional BA and SQP method is presented. The results showed that the hybrid BA-SQP has the advantages of both BA's global search ability and SQP's local search ability, thus enhancing the overall search ability and computational efficiency. For comparison, the results obtained by applying Ant colony optimization algorithm in conditions similar to those of BA are further shown.
Author Roeva, Olympia Nikolaeva
Fidanova, Stefka Stoyanova
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  givenname: Olympia Nikolaeva
  surname: Roeva
  fullname: Roeva, Olympia Nikolaeva
  organization: Bulgarian Academy of Sciences, Institute of Biophysics and Biomedical Engineering
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  givenname: Stefka Stoyanova
  surname: Fidanova
  fullname: Fidanova, Stefka Stoyanova
  email: stefka@parallel.bas.bg
  organization: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
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Snippet In this paper, a hybrid scheme using Bat Algorithm (BA) and Sequential Quadratic Programming (SQP) method is introduced. In the hybrid BA-SQP, the role of BA...
In this paper, a hybrid scheme using Bat Algorithm (BA) and Sequential Quadratic Programming (SQP) method is introduced. In the hybrid BA—SQP, the role of BA...
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SubjectTerms Algorithms
Ant colony optimization
Bat Algorithm
Batch culture
Computer applications
Cultivation
cultivation process
E coli
Escherichia coli
Formicidae
local search
Mathematical models
metaheuristics
Parameter identification
Quadratic programming
Searching
SQP
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Title Hybrid Bat Algorithm for Parameter Identification of an E. Coli Cultivation Process Model
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