Statistical Algorithms for Sustainability Measurement and Decision Making

Selection of Sustainable Process and Essential Indicators for Decision Making Using Machine Learning Algorithms

“…Form the results, it is found that sustainable process selections using clustering theory corroborate that from sustainability footprint (D e ), which uses Euclidian distance. In our previous work, different method of sustainable process selection has been compared for the ASR data (Sikdar et al 2017). Results from sustainability footprint (D e ), vector norm, Canberra distance, zCanberra distance, and Mahalanobis distance show similar ranking of process options in order of their sustainability.…”

“…There are different methods available for selecting sustainable process options by considering the indicators including sustainability footprint (Sikdar et al 2016), analytic hierarchy process (AHP) (Tan and Promentilla 2013), or use of sustainability-weighted return on investment (SWROIM) metric (El-Halwagi 2017). Recently, research on the application of measurement science in sustainability has gained momentum.…”

“…They have adopted the Bprincipal of parsimony^in indicator selection for sustainability assessment in water and sanitation sector. In our previous work, we have used the PLS-VIP method for indicator selection (Mukherjee et al 2013;Sikdar et al 2017). In PLS-VIP, the relative ranking of the indicators was performed in the order of their importance in finding the relative sustainability of the different process options.…”