Mixed-Integer Nonlinear Programming (MINLP) Model for Determining the Optimal Site for a New Industrial Facility with Integrated Economic and Environmental Criteria

A mixed integer nonlinear programming model that affects the water quality in a nearby watershed is presented in this chapter to optimally allocate a new industrial unit. The optimization strategy considers not only the economic factors but also the environmental impact, ensuring that the wastewater streams released into the environment have qualities that guarantee the sustainability of the surrounding watershed. The model was developed using the material flow analysis technique to forecast how the increased dirty discharges will affect the watershed. Consequently, all extractions and outflows are considered, together with the chemical processes occurring within the watershed. The best site for a new industrial plant is determined by combining the watershed model with a disjunctive model. The goal of the objective function is to minimize the annual total cost, which includes the costs associated with treating wastewater and the location-based cost of the new plant (which includes the cost of land and the transportation of goods and services). The watershed's many locations all have different restrictions on the quality of the water. To create a Pareto curve, which illustrates the trade-off between cost and environmental impact, a sensitivity analysis is performed. The model can also be used to determine the incentives required to make less-than-ideal locations appealing enough to warrant the installation of a new plant. The applicability of the suggested method and the efficiency of solving the optimization formulation are demonstrated using two case studies.