Operations-Research Decision Support for Industrial Resource Clusters: A Multi-Objective Linear-Programming Framework for Multi-Origin Water Allocation in a Mediterranean Brewery

Water-intensive industries in the Mediterranean face supply stress and decarbonisation pressure simultaneously. We develop an operations-research decision-support framework that treats the firm as one node of a small industrial resource cluster and prices the cost and carbon-equivalent emissions of five alternative supply trains—municipal water, river water, groundwater, rainwater harvesting and brewery wastewater reuse—within a multi-objective Linear Program. Each train carries engineering-grounded expenditures, energy intensities and grid emissions, and a weighted-sum scalarisation is solved daily for 365 days under three managerial scenarios. On a Cretan microbrewery whose 2022 demand of 5250 m3 is met from the municipal network, the balanced and cost-focused scenarios coincide on a single optimum that cuts the Levelised Cost of Water by 25.3% and emissions by 40.7%, while the eco-friendly scenario yields a 19.3% cost and 51.7% emissions reduction. LP duality, shadow prices and an extended sensitivity programme (diversification, capacity, grid factor, discount rate, RO recovery and demand profile) turn the optimisation into a decision-support package: optimal daily allocations, shadow-price signals on capacity and demand, and robustness diagnostics for capital planning, dispatch and risk management. Results are site-specific, but the framework and its diagnostics transfer in structure to clusters sharing the same convex-polytope source geometry; transposition to energy cooperatives is future work.