1200. Weight Space Decomposition given Extreme Supported Nondominated Points of a Multiobjective Optimization Problem
Invited abstract in session MA-51: Recent advances in multiobjective optimization, stream Multiobjective and vector optimization.
Monday, 8:30-10:00Room: Parkinson B22
Authors (first author is the speaker)
| 1. | Firdevs Ulus
|
| Industrial Engineering, Bilkent University | |
| 2. | Ozlem Karsu
|
| Industrial Engineering, Bilkent University |
Abstract
Weighted sum scalarization (WS) is one of the most well-known scalarization problem for solving multiobjective optimization problems (MOPs). It is possible to find any supported nondominated point by solving WS problem with the corresponding weight parameter from the weight set $W$. For an extreme supported nondominated point $y$, there is a set of weight vectors $W_y \subseteq W$ supporting $y$. Computing $W_y$ for each such $y$ is referred to as weight space decomposition. We propose a methodology for that given the set of extreme supported nondominated points of a MOP using geometric duality results for linear multiobjective optimization. We prove some properties of the weight sets and provide numerical examples.
Keywords
- Multi-Objective Decision Making
- Mathematical Programming
Status: accepted
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