A multiobjective approach for integrated environmental economic planning under uncertainty

This paper proposes an inexact multi-objective mixed integer programming (I MOMIP) approach to deal with the uncertainty and complexity involved in dec ision making for regional sustainable development. The proposed model frame work represents system uncertainty with interval numbers, and addresses com plexity through a multi-objective optimization formulation. Inexact continu ous and discrete decision variables are integrated, therefore enabling the optimal decision regarding sector activity and expansion of the sectors, WW TP, forests, etc., to be made within a holistic optimization framework. The proposed algorithm dissociates the control of each objective, thus allowin g 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 syste m planning for the Haichang Investment Zone (HIZ) in China, and solved unde r two scenarios. The difference between the two solutions indicates that de cision 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 developm ent in the study area.