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Determining the factor levels for a green supply chain using response surface methodology based discrete event simulation

Ayşe Tuğba Dosdoğru (Department of Industrial Engineering, Adana Alparslan Turkes Science and Technology University, Adana, Turkey)
Yeliz Buruk Sahin (Department of Industrial Engineering, Eskisehir Osmangazi University, Eskisehir, Turkey)
Mustafa Göçken (Department of Industrial Engineering, Adana Alparslan Turkes Science and Technology University, Adana, Turkey)
Aslı Boru İpek (Department of Management Information Systems, Kütahya Dumlupınar University, Kutahya, Turkey)

Kybernetes

ISSN: 0368-492X

Article publication date: 14 May 2024

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Abstract

Purpose

This study aims to optimize the levels of factors for a green supply chain (GSC) while concurrently gaining valuable insights into the dynamic interrelationships among several factors, leading to reductions in CO2 emissions and the maximization of the average service level, thereby enhancing overall supply chain performance.

Design/methodology/approach

Response surface methodology (RSM) is employed as a technique for multiple response optimization. This study uses a supply chain simulation model that includes decision variables related to the level of inventory control parameters and vehicle capacity. The desirability approach is adopted to achieve optimization objectives by focusing on minimizing CO2 emissions and maximizing service levels while simultaneously determining the optimum levels of considered decision variables.

Findings

The high R2 values of 97.38% for CO2 and 97.28% for service level, along with adjusted R2 values reasonably close to predicted values, affirm the models' capability to predict responses accurately. Key significant model terms for CO2 encompassed reorder point, order up to quantity, vehicle capacity, and their interaction effects, while service level is notably influenced by reorder point, order up to quantity, and their interaction effects. The study successfully achieved a high level of desirability value of %99.1 and the validated performance levels confirmed that the results fall within the prediction interval.

Originality/value

This study introduces a metamodel framework designed to optimize various design parameters for a GSC combining discrete event simulation (DES) and RSM in the form of a simulation optimization model. In contrast to the literature, the current study offers an exhaustive and in-depth analysis of the structural elements of the supply chain, particularly the inventory control parameters and vehicle capacity, which are crucial for comprehending its performance and environmental impact.

Keywords

Citation

Dosdoğru, A.T., Buruk Sahin, Y., Göçken, M. and Boru İpek, A. (2024), "Determining the factor levels for a green supply chain using response surface methodology based discrete event simulation", Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-08-2023-1488

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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