South Carolina counties use a mixed-integer programming-based decision support tool for planning municipal solid waste management

Constructing an integrated municipal solid waste management plan and implementing the strategy is becoming increasingly important. We constructed a mixed-integer programming model to support this planning effort in several South Carolina counties; however, we encountered a number of problems in moving the optimal solution into the decision-making process. Most of these problems emanated from the fact that people making policy decisions know that many factors must be considered that are not part of an economic model. We discovered that understanding the decision-making process was key to having the optimal solution used during planning. This understanding led us to construct a spreadsheet-based model to serve as an interface between the optimization model and the decision makers. As such, the planning effort was greatly enhanced by the information contained in the optimization model, but it included all the other factors that are important to communities but are not modeled. We provide the actual results from one county as a case study.