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Teaching Learning Based Optimization Algorithm [electronic resource] : And Its Engineering Applications / by R. Venkata Rao.

By: Rao, R. Venkata [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Cham : Springer International Publishing : Imprint: Springer, 2016Description: XVI, 284 p. 32 illus., 14 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319227320.Subject(s): Engineering | Computer-aided engineering | Computer mathematics | Engineering design | Engineering | Engineering Design | Computer-Aided Engineering (CAD, CAE) and Design | Computational Science and EngineeringAdditional physical formats: Printed edition:: No titleDDC classification: 620.0042 Online resources: Click here to access online
Contents:
Introduction to optimization -- Advanced optimization techniques -- Elitist and Modified TLBO algorithms -- Applications of proposed E-TLBO and M-TLBO algorithms on constrained and unconstrained benchmark functions -- Design optimization of heat exchangers -- Design optimization of rotary regenerators -- Design optimization of cooling tower -- Optimization of combined Brayton and inverse Brayton cycle -- Design optimization of two-stage thermoelectric cooler -- Process parameter optimization of manufacturing processes using TLBO algorithm -- Design optimization of machine elements using TLBO algorithm and its versions -- Applications of TLBO algorithm in electrical engineering discipline -- Applications of TLBO algorithm in computer engineering discipline -- Applications of TLBO algorithm in civil and structural engineering disciplines -- Concluding remarks.
In: Springer eBooksSummary: Describing a new optimization algorithm, the "Teaching-Learning-Based Optimization (TLBO)," in a clear and lucid style, this book maximizes reader insights into how the TLBO algorithm can be used to solve continuous and discrete optimization problems involving single or multiple objectives. As the algorithm operates on the principle of teaching and learning, where teachers influence the quality of learners' results, the elitist version of TLBO algorithm (ETLBO) is described along with applications of the TLBO algorithm in the fields of electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics and biotechnology. The book offers a valuable resource for scientists, engineers and practitioners involved in the development and usage of advanced optimization algorithms.
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Introduction to optimization -- Advanced optimization techniques -- Elitist and Modified TLBO algorithms -- Applications of proposed E-TLBO and M-TLBO algorithms on constrained and unconstrained benchmark functions -- Design optimization of heat exchangers -- Design optimization of rotary regenerators -- Design optimization of cooling tower -- Optimization of combined Brayton and inverse Brayton cycle -- Design optimization of two-stage thermoelectric cooler -- Process parameter optimization of manufacturing processes using TLBO algorithm -- Design optimization of machine elements using TLBO algorithm and its versions -- Applications of TLBO algorithm in electrical engineering discipline -- Applications of TLBO algorithm in computer engineering discipline -- Applications of TLBO algorithm in civil and structural engineering disciplines -- Concluding remarks.

Describing a new optimization algorithm, the "Teaching-Learning-Based Optimization (TLBO)," in a clear and lucid style, this book maximizes reader insights into how the TLBO algorithm can be used to solve continuous and discrete optimization problems involving single or multiple objectives. As the algorithm operates on the principle of teaching and learning, where teachers influence the quality of learners' results, the elitist version of TLBO algorithm (ETLBO) is described along with applications of the TLBO algorithm in the fields of electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics and biotechnology. The book offers a valuable resource for scientists, engineers and practitioners involved in the development and usage of advanced optimization algorithms.

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