Robust Targeting of Resource Requirement in a Continuous Water Network

Abstract

In this paper, a robust formulation is proposed to calculate the target of freshwater requirement as a resource for continuous processes in industries. The proposed robust counterpart linear programming formulation includes resource minimization constraints and has been applied to optimize the external resource, to satisfy unmet demands in source-sink water allocation problems, with deterministic flows and deterministic quality. Compared to the traditional-scenario-based stochastic programming method, a robust counterpart optimization method has a unique advantage. The scale of the corresponding optimization problem does not increase exponentially with the number of uncertain parameters. Robust optimization applicability has been applied to resource management networks with uncertain qualities and flows for the application of individual sources and demands with the desired reliability. The resultant formulation preserves the linearity of the mathematical model and can control the degree of conservatism for every constraint and guarantees feasibility for the problem. Decision-makers can also make a trade-off between uncertainty level and an upper probability of constraint violation. This model will assist the planner to decide the water requirement under uncertain conditions and to do the necessary preparation accordingly and immunes the process against uncertainties to satisfy demands.