Demonstration of two multi-objective optimization strategies

Application of the weighted sum and epsilon-constraint methods for multi-objective optimization


Updated 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:
See the _readme.txt file to get started.

Cite As

James Allison (2023). Demonstration of two multi-objective optimization strategies (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2015b
Compatible with any release
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