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The importance of supply chain management in analyzing and later catalyzingeconomic expectations while simultaneously prioritizing cleaner productionaspects is a vital component of modern finance. Such predictions, though, areoften known to be less than accurate due to the ubiquitous uncertainty plaguingmost business decisions. Starting from a multi-dimensional cost functiondefining the sustainability of the supply chain (SC) kernel, this articleoutlines a 4-component SC module - environmental, demand, economic, and socialuncertainties - each ranked according to its individual weight. Ourmathematical model then assesses the viability of a sustainable business byfirst ranking the potentially stochastic variables in order of their subjectiveimportance, and then optimizing the cost kernel, defined from a utilityfunction. The model will then identify conditions (as equations) validating thesustainability of a business venture. The ranking is initially obtained from anAnalytical Hierarchical Process; the resultant weighted cost function is thenoptimized to analyze the impact of market uncertainty based on our supply chainmodel. Model predictions are then ratified against SME data to emphasize theimportance of cleaner production in business strategies.

Cleaner Production in Optimized Multivariate Networks: Operations Management through a Roll of Dice