Author(s): Gomes, Luís ; Vieira, António ; Fragoso, Rui ; Luís, Coelho ; Neves, José ; Almeida, Dora
Date: 2024
Persistent ID: http://hdl.handle.net/10174/36241
Origin: Repositório Científico da Universidade de Évora
Subject(s): Simulation; Multi-objective simulation-optimization; Data envelopment analysis; Supply chain design; Decision-making; Efficiency
Decision-making in multi-objective problems is a complex problem with several approaches existing in the literature. Many such approaches typically com bine simulation and optimization methods to achieve a robust tool capable of provid ing useful information to decision-makers. While simulation helps decision-makers to test alternative scenarios and allows uncertainty to be considered, optimization enables them to find the best alternatives for specific conditions. This paper pro poses an alternative approach consisting of three levels, wherein we use simulation to model complex scenarios, simulation-optimization to identify the scenarios of the Pareto-front, and Data Envelopment Analysis to identify the most efficient solutions, including those not belonging to the Pareto-front, thereby exploiting the benefits of efficiency analysis and simulation-optimization. This can be useful when decision makers decide to consider scenarios that, while not optimum, are efficient for their decision-making profile. To test our approach, we applied it to a supply chain design problem. Our results show how our approach can be used to analyze a given system from three different perspectives and that some of the solutions, while not optimum, are efficient. In traditional approaches, such scenarios could be overlooked, despite their efficiency for specific decision-making profiles
