Introduction
Synopsis
Optimisation involves finding the ‘best’ solution according to specified criteria. In Engineering Design, this might typically be minimum cost or weight, maximum quality or efficiency, or some of the performance index pertaining to a disciplinary objective. Realistic optimal design involves not only an objective function to be minimized or maximized, but also constraints that represent limitations on the design space. Numerical programming requires the mathematical representation of the design space (objective function and constraints) in terms of ‘design variables- (parameters that signify some potential for change) Generally the problem of interest in engineering are of a non-linear nature, in that the dependence of the objective function and constraints on the design variables is non-linear.’ This course introduces the traditional optimisation methods that can be used to solve a wide range of problems across all engineering disciplines as well as advanced optimization methods. By the end of the semester the student will have gained a basic knowledge of numerical optimisation algorithms and will have sufficient understanding of the strengths and weakness of these algorithms to apply them appropriately in engineering design.
Lecture Notes
Day 3
Additional Notes
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