The role of simulation and optimization methods in supply chain risk management: Performance and review standpoints

Oliveira, Josenildo Brito De; Jin, Mingzhou; Lima, Renato da Silva; Kobza, John E.; Montevechi, José Arnaldo Barra

doi:10.1016/j.simpat.2018.11.007

Cited by 89 publications

(51 citation statements)

References 144 publications

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“…Some literature is conducted to reveal the priority of DM on the condition that proper algorithms are used to deal with the logistics problems [34,35], while other scholars and institutions have applied the relevant data mining methods to the field of logistics, [36][37][38][39]. Most of the studies, however, concentrate on the area of monolithic supply chain management, not specific enough, and the analyses of the S&D issue are always fragmented since the demand can be commonly postulated through the regression and prediction DM algorithm while the supply is hard to define and measure.…”

Section: Data Mining Algorithmmentioning

confidence: 99%

Integrated Data Mining and TOPSIS Entropy Weight Method to Evaluate Logistics Supply and Demand Efficiency of a 3PL Company

Yan

Gong

et al. 2020

Mathematical Problems in Engineering

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In the past decades, despite considerable attention having been paid to third-party logistics (3PL) owing to its specialized service, sophisticated operation, and reduced cost, research on quantitative methods for estimating the efficiency of 3PL companies is still lacking, especially for those with small or medium scale. Therefore, the purpose of this study was to establish a quantitative evaluation method to measure the efficiency of the individual nongovernmental 3PL firms and explore the valuable information for the management of 3PL business with Apriori and K-means. Taking TopChains (an emerging nongovernmental 3PL company) as an example, the monthly supply and demand (S&D) level and matching degree were evaluated via the integrating data mining algorithm (i.e., Apriori and K-means) and TOPSIS entropy weight method based on historical data. The findings demonstrate that the S&D level varied with time and space, and the customer demand in February tended to reduce substantially. Besides, the outcome of S&D matching degree in June is undesirable, indicating the unsatisfactory efficiency in resource management. The evaluation maneuver stated in this study can serve as a valuable tool to measure individual nongovernmental 3PL enterprises’ efficiency in terms of S&D, and for reference, the results can aid in rational enterprise investment plan. Besides, this attempt broadened the direction of ARM and K-means being applied in the logistics field.

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Section: Data Mining Algorithmmentioning

confidence: 99%

Integrated Data Mining and TOPSIS Entropy Weight Method to Evaluate Logistics Supply and Demand Efficiency of a 3PL Company

Yan

Gong

et al. 2020

Mathematical Problems in Engineering

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“…De igual modo Oliveira et al (2019) abordan la problemática de plantear estrategias para mitigar el riesgo, concluyendo que no hay una alineación entre la respuesta al riesgo y los enfoques de solución del riesgo, ya que las estrategias de respuesta al riesgo deben ser coherentes con las soluciones para mitigar el riesgo. Este estudio analiza la aplicación de herramientas de simulación, modelos de optimización y sistemas de medición de rendimiento para la gestión del riesgo de la cadena de suministro.…”

Section: Cadena De Suministro Verdeunclassified

“…Respecto a la simulación y optimización, los autores proponen el uso de los métodos de simulación para reproducir la dinámica del riesgo y los impactos del riesgo, y el uso de modelos para la gestión del riesgo como el de la colonia de hormigas (Ant Colony) y el método de intersección de límites normales (Normal Boundary Intersection). Dado que no se encontraron estos métodos en los artículos revisados, Oliveira et al (2019) sugieren que se mejore la perspectiva de la optimización basada en la simulación, además propone que se desarrollen medidas de riesgo basadas en Seis Sigma para evaluar los impactos críticos del riesgo en el rendimiento de la cadena de suministro.…”

Section: Cadena De Suministro Verdeunclassified

Un análisis de revisiones de modelos y algoritmos para la optimización de planes de aprovisionamiento, producción y distribución de la cadena de suministro

Guzmán

Mula

Andrés

2020

DyO

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El propósito de este artículo es analizar los diferentes modelos y algoritmos utilizados para la optimización de planes de aprovisionamiento, producción y distribución en la cadena de suministro a través de las últimas revisiones de la literatura realizadas en este campo. Este estudio pretende proporcionar a los investigadores un punto de partida para la selección de modelos y algoritmos para la resolución de este tipo de problemas en la cadena de suministro y presentar varias líneas de investigación futuras.Palabras clave: Cadena de suministro; planificación; optimización; modelos; algoritmos; revisión de la literatura

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“…In order to evaluate the results of the production process improvement using simulation, the references [59][60][61][62] recommend the evaluation of lean performance by using seven key performance indicators (KPI) presented in Table 1, from which three indicators specific to the problem to be solved will be used. Of the seven indicators referring to Table 1, VSM allows to deal with three of them: people productivity (PP), value added per person (VAPP), and percent of use of production space (FSU) [30].…”

Section: Evaluation Of Lean Performance For the Vsm Target Simulationmentioning

confidence: 99%

Agent-Based Simulation of Value Flow in an Industrial Production Process

et al. 2019

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The current competitive environment demands companies to be more and more efficient. In order to increase manufacturing efficiency, two apparently independent approaches have emerged: lean strategies, focusing on identifying and minimizing non-added value activities, identifying wastes in the system and their elimination, and information tools for planning and controlling activities. In this paper, a manufacturing system was considered for which it was necessary to increase the production capacity in order to respond to the customer’s increased demand. A practical case study in the automotive industry for a medium-sized enterprise was considered. In order to investigate the production process parameters and to implement lean principles, Value Stream Mapping (current analysis and optimized solution) and Anylogic agent-based simulations were carried out. Based on this, the lean performances, specific for the target VSM, were evaluated in terms of key performance indicators. The benefits of integrating agent-based simulation in the design and analysis of the value flow in the production chain are the capitalization of the information offered by Value Stream Mapping and the possibility to choose the best one from the possible scenarios. It generates important time and cost reductions without further resource waste.

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The role of simulation and optimization methods in supply chain risk management: Performance and review standpoints

Cited by 89 publications

References 144 publications

Integrated Data Mining and TOPSIS Entropy Weight Method to Evaluate Logistics Supply and Demand Efficiency of a 3PL Company

Integrated Data Mining and TOPSIS Entropy Weight Method to Evaluate Logistics Supply and Demand Efficiency of a 3PL Company

Un análisis de revisiones de modelos y algoritmos para la optimización de planes de aprovisionamiento, producción y distribución de la cadena de suministro

Agent-Based Simulation of Value Flow in an Industrial Production Process

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