Computer Aided Methods in Optimal Design and Operations : Vilnius, Lithuania.

This book covers different topics on optimal design and operations with particular emphasis on chemical engineering applications. A wide range of optimization methods - deterministic, stochastic, global and hybrid - are considered. Containing papers presented at the bilateral workshop by British and...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Bogle, I. D. L.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Singapore : World Scientific Publishing Company, 2006.
Colección:Series on computers and operations research.
Temas:
Computer-aided design > Congresses.
Mathematical optimization > Congresses.
Control theory > Congresses.
Chemical engineering > Mathematical models > Congresses.
Conception assistée par ordinateur > Congrès.
Optimisation mathématique > Congrès.
Théorie de la commande > Congrès.
Génie chimique > Modèles mathématiques > Congrès.
Chemical engineering > Mathematical models
Computer-aided design
Control theory
Mathematical optimization
Conference papers and proceedings
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Preface; Contents; Hybrid Methods for Optimisation; 1. Introduction; 2. Hybrid Methods for Optimisation; 3. Embedded Hybrid Methods; 4. Sequential Hybrid Methods; 5. Illustrative Case Study; 6. Discussion; References; An MILP Model for Multi-class Data Classification; 1. Introduction; 2. Problem Statement and Mathematical Formulation; 3. Testing Procedure; 4. An Iterative Solution Algorithm; 5. Computational Results; 6. Conclusions; References; Implementation of Parallel Optimization Algorithms Using Generalized Branch and Bound Template; 1. Introduction; 2. General Branch and Bound Algorithm.
  • 3. BB Algorithm Template4. Conclusions; References; Application of Stochastic Approximation in Technical Design; 1. Introduction; 2. Formulation of the Optimization Problem; 3. Computer Modelling; 4. Application of Order Statistic to Optimality Testing; 5. Computer Modelling; 6. Conclusion; References; Application of the Monte-Carlo Method to Stochastic Linear Programming; 1. Introduction; 2. Stochastic Differentiation and Monte-Carlo Estimators; 3. Stochastic Procedure for Optimisation; 4. Statistical Testing of the Optimality Hypothesis; 5. Computer Study; 6. Discussion and Conclusions.
  • 2. Particle Size Distribution Modelling and Numerical Solution3. Open-loop Control Studies; 4. Pareto Optimisation; 5. Conclusions; References; Application of Parallel Arrays for Parallelisation of Data Parallel Algorithms; 1. Introduction; 2. Parallel Programming Tools and Standards; 3. ParSol Features; 4. ParSol Structure and Usage; 5. Application of Par Sol to Porous Media Problem Solver; 6. Application of ParSol to Image Smoothing; 7. Conclusions; References; CAD Grammars: Extending Shape and Graph Grammars for Spatial Design Modelling; 1. Introduction; 2. Shape Grammars.

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