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4352. A methodology to tackle multi-objective linear programming problem
Invited abstract in session WA-12: YW4OR_1, stream WISDOM - Women in OR.
Wednesday, 8:30-10:00Room: 13 (building: 116)
Authors (first author is the speaker)
| 1. | Mariana Mesquita-Cunha
|
| Departamento de Engenharia e Gestão, Instituto Superior Técnico, Universidade de Lisboa |
Abstract
Multi-objective decision-making often poses challenges due to the computational complexity of generating and analyzing the Pareto front. To address this, we propose a framework integrating two strategies to alleviate the burden on decision-makers (DMs). Firstly, we introduce algorithms based on the epsilon-constraint method to derive a Pareto front representation balancing coverage, uniformity, and cardinality, thereby reducing the number of non-dominated vectors to be considered. Secondly, we incorporate DM preferences to refine the feasible region. We do so initially using criteria ranking and selecting a region of interest of the Pareto front to focus the representation. Then, after generating the initial representation, through pairwise comparisons we construct convex cones and eliminate inferior regions from consideration. We demonstrate the efficacy of our framework through its application to pharmaceutical supply chain design, illustrating its adaptability aid in tactical and strategic decision-making contexts. This methodology offers a practical approach to multi-objective optimization challenges, providing DMs with manageable decision support while maintaining focus on the proposed strategies
Keywords
- Multi-Objective Decision Making
Status: accepted
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