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Can I read Process Design Optimisation Using Embedded Hybrid Visualisation and Data Analysis Techniques Within a Genetic Algorithm Optimisation Framework on EtoBox?
Process Design Optimisation Using Embedded Hybrid Visualisation and Data Analysis Techniques Within a Genetic Algorithm Optimisation Framework by K. Wang; A. Salhi; E.S. Fraga is a Engineering article available to read on EtoBox.
What is Process Design Optimisation Using Embedded Hybrid Visualisation and Data Analysis Techniques Within a Genetic Algorithm Optimisation Framework about?
Process optimisation is a difficult task due to the non-linear, non-convex and often discontinuous nature of the mathematical models used. Although significant advances in deterministic methods have been made, stochastic procedures, specifically genetic algorithms, provide an attractive technology for solving these optimisation problems. However, genetic algorithms are not naturally suited to highly constrained problems. We propose a targeted genetic algorithm for process optimisation which is suitable for highly constrained problems. The genetic operators, crossover and mutation, are defined based on information gained about the feasible region and the behaviour of the objective function through the use of a data analysis procedure. The data analysis is based on a visual representation, the parallel co-ordinate system. A pattern matching algorithm, the Scan Circle Algorithm [K.
Who reads Process Design Optimisation Using Embedded Hybrid Visualisation and Data Analysis Techniques Within a Genetic Algorithm Optimisation Framework?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- K. Wang; A. Salhi; E.S. Fraga
- Publisher
- Elsevier Science; Elsevier ; Elsevier BV (ISSN 0255-2701)
- Published
- 2004
- Language
- EN
- Field
- Engineering (Physical Sciences)