 This implies that \(\alpha_n\) is strictly better than \(\alpha_m\) by at least one criterion in \(k_p \in K\), and it not worse than \(\alpha_m\) by any criterion \(k_i \in K\). An alternative \(\alpha_i \in A\) is non-dominated if, and only if, it is not dominated by any other element of \(A\). Thus, using multi-criteria analysis, we attempt to find a non-dominated set of alternatives from which to design conservation area networks. An example from Sarkar (2012: 204–6) is briefly considered. We begin with place prioritization with 100 attempts to create a prioritized lists of hexagons for a target of 10 representatives for each vertebrate species present in Texas. There were thirty-two feasible solutions—ones that satisfied the conservation target. However, two other criteria were used for multi-criteria analysis, economic cost and social cost. The first was estimated by the cost of the conservation plan per hexagon and the second was estimated by the human population size of each hexagon included. From the thirty-two feasible solutions, there were only two non-dominated solutions selected by the multi-criteria analysis.