Coupling fuzzy-chance constrained program with minimax regret analysis for water quality management

Mathematical modeling technique plays an important role for regionalization assessment of integrated economy and environment problems, resulting in provision of decision makers with break-through insights and risk-informed strategies. However, such a planning effort is complicated with a variety of uncertain and dynamic factors as well as their interactions. In this study, a fuzzy-chance constrained programming (FCP) method is firstly developed for addressing uncertainties characterized as fuzzy sets and random variables and, then, minimax regret (MMR) analysis technique is advanced to determine desired alternative that can reflect compromises between maximized system benefit and minimized system-failure risk. FCP coupled with MMR is applied to a real-case study of water quality management through optimizing chemical industry activities of the New Binhai District, an economically and industrially fast growing region in the center of northern China. Modeling formulation can analyze interactions among criteria of industry layout, economic benefit, pollution mitigation, and water quality security. Solutions for planning the water quality management have been generated, reflecting that there is trade-off among industrial structure, environmental protection, and economic development.