Demonstration of two multi-objective optimization strategies

Version 1.0.0.0 (6,2 ko) par James Allison
Application of the weighted sum and epsilon-constraint methods for multi-objective optimization
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Mise à jour 21 oct. 2017

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Created for use in introductory design optimization courses (e.g., SE 413 at UIUC). Demonstrates that the epsilon-constraint method can identify non-dominated points on a Pareto frontier corresponding to a multi-objective optimization problem, whereas the more well-known weighted sum method cannot. The test problem is adapted from:
"Optimization in Practice with MATLAB: For Engineering Students and Professionals", A. Messac, 2015, Cambridge University Press
MathWorks partner webpage for text:
https://www.mathworks.com/support/books/book106117.html
See the _readme.txt file to get started.

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James Allison (2024). Demonstration of two multi-objective optimization strategies (https://www.mathworks.com/matlabcentral/fileexchange/64787-demonstration-of-two-multi-objective-optimization-strategies), MATLAB Central File Exchange. Récupéré le .

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