Stochastic Pinch Analysis to address multi-objective resources conservation problems with parametric uncertainties.

An emphasis on sustainable growth helps decrease the initial capital and reduce the impact of industry on an ecologically sensitive environment through resource conservation. Pinch Analysis serves as a valuable tool to identify the potential for resource conservation, waste minimization, and resource costs. However, there are inherent uncertainties associated with these resource conservation networks. The concept of Pinch Analysis is broadened to multi-objective resource conservation problems incorporating parametric uncertainties in this paper. The objective functions are combined to form a single compound objective function using the weighted sum approach. For the compound objective function, prioritized sequences (or resource combinations) are generated through multi-objective prioritized costs to accommodate parametric uncertainties. The multi-objective prioritized cost vs. weights curve helps determine the unique prioritized sequences for different range of weights to achieve optimal solutions. An exact analytical expression for the maximum number of prioritized sequences is also derived. Furthermore, a method is presented to construct the complete Pareto-optimal front to represent all optimal solutions graphically. Two illustrative examples, the hydrogen conservation problem with two objectives (cost and emission) and the water conservation problem with three objectives (cost, land requirement, and emission), demonstrate the proposed method's utility and efficacy. A multi-objective resource conservation problem under normally distributed parametric uncertainties. [Display omitted] • Included parametric uncertainties in multi-objective resource conservation problems. • Stochastic Pinch Analysis minimizes multiple objectives with multiple resources. • Determined the maximum number of possible prioritized sequences of resources. • Proposed multi-objective prioritized cost to determine the optimal sequence. • Determined Pareto-optimal fronts to represent all the efficient solutions. [ABSTRACT FROM AUTHOR]