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Abstract
This paper proposes an inexact multi-objective mixed integer programming (IMOMIP) approach to deal with the uncertainty and complexity involved in decision making for regional sustainable development. The proposed model framework represents system uncertainty with interval numbers, and addresses complexity through a multi-objective optimization formulation. Inexact continuous and discrete decision variables are integrated, therefore enabling the optimal decision regarding sector activity and expansion of the sectors, WWTP, forests, etc., to be made within a holistic optimization framework. The proposed algorithm dissociates the control of each objective, thus allowing convenient interaction between the model and decision makers, as well as an efficient compromise between the competing objectives.
The IMOMIP method is applied to the integrated economic environmental system planning for the Haichang Investment Zone (HIZ) in China, and solved under two scenarios. The difference between the two solutions indicates that decision makers’ preference has significant influence on the model's behavior. However, both scenarios’ solutions achieve reasonable compromise between all objectives, including economic benefit, water resources, and water and air quality, thus providing potential alternatives for sustainable development in the study area.