An MINLP Model for the Optimal Location of a New Industrial Plant with Simultaneous Consideration of Economic and Environmental Criteria
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- 作者：Luis Fernando Lira-Barraga虂n ; Jose虂 Mari虂a Ponce-Ortega ; Medardo Serna-Gonza虂lez ; Mahmoud M. El-Halwagi
- 刊名：Industrial & Engineering Chemistry Research
- 出版年：2011
- 出版时间：January 19, 2011
- 年：2011
- 卷：50
- 期：2
- 页码：953-964
- 全文大小：321K
- 年卷期：v.50,no.2(January 19, 2011)
- ISSN：1520-5045
文摘
This paper presents a new mixed-integer nonlinear programming model for the optimal allocation of a new industrial plant which impacts the water quality throughout a surrounding watershed. In addition to the economic aspects, the optimization approach also accounts for the environmental impact, such that the wastewater streams discharged to the environment have characteristics that ensure the sustainability of the surrounding watershed. The model was formulated to predict the behavior for the watershed impacted for the new polluted discharges through the material flow analysis technique. Therefore, all discharges and extractions are considered as well as the chemical reactions that take place in the watershed. The watershed model is combined with a disjunctive model for the optimal location of a new industrial plant and the selection of the type of treatment. The objective function is aimed at minimizing the total annual cost, which includes the wastewater treatment costs and the location-based cost of the new plant (including the transportation of raw materials, products, and services, as well as the land cost). The constraints on water quality are imposed at various locations throughout the watershed. A sensitivity analysis is carried out to generate the noninferior curve that shows the trade-off between cost and environmental impact. Furthermore, the model can be used to identify incentives needed for nonoptimal locations to become attractive enough to install the new plant. Two example problems were used to show the applicability of the proposed methodology and the effectiveness of solving the optimization formulation.