@article { author = {Rezaei, Mahdi and Akbarpour Shirazi, Mohsen and karimi, Behrooz}, title = {A multi-objective SCOR-based decision alignment for supply chain performance management}, journal = {Scientia Iranica}, volume = {25}, number = {5}, pages = {2807-2823}, year = {2018}, publisher = {Sharif University of Technology}, issn = {1026-3098}, eissn = {2345-3605}, doi = {10.24200/sci.2017.4463}, abstract = {A dynamic integrated solution for three main problems through integrating all metrics using SCOR are proposed in this research. This dynamic solution comprises strategic decisions in high-level, operational decisions in low-level and alignment of these two decision levels. In this regard, a human intelligence-based process for high level decisions and machine-intelligence based decision support systems (DSSs) for low-level decisions is then proposed using a novel approach. The operational presented model considers important supply chain features thoroughly such as different echelons, several suppliers, several manufacturers and several products during multiple periods. A multi-objective mathematical programming model is then developed to yield the operational decisions with Pareto efficient performance values and solved using a well-known meta-heuristic algorithm, i.e., NSGAII where its parameters is tuned using Taguchi method. Afterward, an intermediate machine-intelligence module is used to determine the best operational solution based on the strategic decision maker’s idea. The efficiency of the proposed framework is shown through numerical example where a sensitivity analysis is then conducted over the obtained results so as to show the impact of the strategic scenario planning on the considered supply chain’s performance.}, keywords = {Multi-objective,NSGAII,SCOR Model,Decision alignment,Supply chain,performance management}, url = {https://scientiairanica.sharif.edu/article_4463.html}, eprint = {https://scientiairanica.sharif.edu/article_4463_59258a5536e2659708dfa6c8eb8b3e0d.pdf} }