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1847. Weight Space Decomposition for Multiobjective Linear Programming in the Context of Equitable Optimization
Invited abstract in session TA-37: Objective Space-Based Approaches in Multiobjective Optimization, stream Multiobjective Optimization.
Tuesday, 8:30-10:00Room: 33 (building: 306)
Authors (first author is the speaker)
| 1. | Firdevs Ulus
|
| Industrial Engineering, Bilkent University | |
| 2. | Ozlem Karsu
|
| Industrial Engineering, Bilkent University |
Abstract
We consider equitable linear optimization problems (ELOP), which are multiobjective optimization problems, with each objective representing the benefit that one entity receives. In such problems, the concept of dominance is replaced by equitable dominance. The aim is to find the set of equitably nondominated points, which can be done by solving ordered weighted averaging (OWA) scalarization. Each solution corresponds to a different set of weights that make the solution optimal, hence a different degree of inequity aversion. We discuss a novel use of the parametric simplex algorithm to address ELOP. The algorithm not only provides the set of equitably nondominated solutions but also yields the corresponding weight space decomposition. We also propose an alternative method based on geometric duality to compute the weight space decomposition given the set of nondominated solutions.
Keywords
- Programming, Multi-Objective
- Programming, Linear
- Multi-Objective Decision Making
Status: accepted
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