Publicado

2018-07-01

Simulation-optimization techniques for closed-loop supply chain design with multiple objectives

Técnicas de simulación-optimización para el diseño de cadenas de abastecimiento de ciclo cerrado con múltiples objetivos

DOI:

https://doi.org/10.15446/dyna.v85n206.70596

Palabras clave:

supply chain design, risk, sustainability, simulation (en)
diseño de cadena de abastecimiento, riesgo, sostenibilidad, simulación (es)

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Autores/as

This paper presents a methodology for determining the optimal supply chain design with economic, environmental and risk management considerations. A multi-objective model based on mixed integer programming is proposed seeking three objectives: First, to minimize the total cost of transportation and the costs associated to the use of intermediate nodes. Second, to minimize the risks of product losses in transportation. Third, to minimize the environmental impact of CO2 emissions produced by transportation and storage operations. The proposed model is solved with two approaches: First, a commercial solver to compute the Pareto-optimal set of solutions. Second, a simulation-based optimization approach that allows to obtain statistically different but efficient solutions such that the decision-maker will be able to trade-off objectives while considering only Pareto optimal solutions. Experiments on random instances demonstrate the capability of the models and methods.
El objetivo de este trabajo es determinar el diseño óptimo para una cadena de suministro de tres eslabones de acuerdo a consideraciones económicas, ambientales y de gestión de riesgo. Se plantea un modelo de programación entera mixta que busca simultáneamente: Primero, minimizar el costo total del transporte y el costo asociado al uso de nodos intermedios; Segundo, minimizar las pérdidas de producto en el transporte como factor de riesgo; Tercero, minimizar el impacto ambiental por emisiones de CO2 en cada una de las conexiones y nodos. El modelo se resuelve utilizando un método exacto y métodos de optimización vía simulación que permiten obtener distintas soluciones de tal manera que el usuario podrá escoger de acuerdo a sus prioridades. Experimentos en instancias aleatorias demuestran la capacidad de los modelos y métodos propuestos.

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[1]
W. J. Guerrero, L. A. Sotelo-Cortés, y E. Romero-Motta, «Técnicas de simulación-optimización para el diseño de cadenas de abastecimiento de ciclo cerrado con múltiples objetivos», DYNA, vol. 85, n.º 206, pp. 202–210, jul. 2018, doi: 10.15446/dyna.v85n206.70596.

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