Archives > Volume 15 | Number 2 | June 2020 > pp 151–163
Advances in Production Engineering & Management
Volume 15 | Number 2 | June 2020 | pp 151–163
Multi-criteria decision making in supply chain management based on inventory levels, environmental impact and costs
Žic, J.; Žic, S.
ABSTRACT AND REFERENCES (PDF) |
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A B S T R A C T
Supply chains in a global business environment operate within conflicting aspects. This research analyses correlation and interdependencies between inventory levels, costs and greenhouse gas emissions from replenishments within supply chain echelon. A simulation-based inventory optimisation conducted on 4000 experiments assumes the conditions of stochastic market demand, (R, s, S) inventory policy, target fill rates, predefined lead times and closing days constraint. It verifies the influence of operational and logistic decisions such as frequency of inventory replenishments or vehicle size selection on management objectives. Besides determining the best individual results for the objectives of minimum inventory levels, total costs and emissions, the overall best solutions in terms of three decision models - uniformly valued, cost-oriented and environmentally responsible model, were determined using multi-criteria decision-making methodology. These models are relevant for both scientific and practical managerial settings due to the evident lack of research simultaneously analysing inventory, cost and environmental performances of (R, s, S) policy. This study confirms that it is crucial in practice to perform an extensive simulation experiment analysis for each product to be able to determine its optimal settings. Inventory management software should have a direct influence on operational decisions in order to reduce costs or emissions within the same fill rate.
A R T I C L E I N F O
Keywords • Green supply chain; Multi-criteria decision making; Environmental impact; Costs; Inventory levels
Corresponding author • Žic, J.
Article history • Received 17 March 2020, Revised 17 July 2020, Accepted 20 July 2020
Published on-line • 31 July 2020
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