Sustainable supply network design through optimisation with clustering technique integration

Abstract

Network complexity between elements in large data sets reduces the group's feasibility for single element analysis in regards to time and cost. Clustering of elements into several minor groups allows the display of clearer group's development and introduction of simpler yet centralised industrial management. The clustering of engineering facilities, particularly, allows the analysis of industrial business development and network links among the engineering facilities in the cluster. In this work, a demonstrating case study on biomass utilisation is developed for optimised supply network design. The facilities are grouped into clusters for industrial management based on their material interactions. The material supply and process network is optimised economically and its environmental emission is taken into consideration. The processing facilities are interacted through industrial symbiosis approach. The flexibility of the model is improved with the model's capacity to allocate external interruption (e.g., potential investments). This work incorporates the economic, environmental and social aspects in the industrial supply network design.