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The MOLA procedure is easy to understand and thus very well suited for participatory decision making processes. Furthermore, it is fast and capable of processing large data sets. Although we examined only two conflicting objectives, the 2D decision space could be extended to a multi-dimensional space representing many conflicting objectives. However, with more than three objectives the approach loses its graphic simplicity and becomes harder to interpret.
The MOLA-approach is not the only way to allocate land use. Almost any optimization technique can be used. Another commonly used approach within the GIScience field is called linear programming. Linear programming is a method of finding an optimal solution to problems that require several factors to be balanced against each other. In our case these factors are conflicting land-use objectives. Thus, linear programming for land-use allocation is used to achieve optimal land-use, where defined objectives can be maximized and constraints are respected. It is called linear programming because the optimization is achieved by optimizing a set of linear functions representing the decision variables.
The further reading section of this unit gives you some starting points to explore the literature on linear programming with GIS.