Seriation is a data analytic tool for obtaining a permutation of a set of objects with the goal of revealing structural information within the set of objects. Seriating variables, cases or categories generally improves visualisations of statistical data, for example, by revealing hidden patterns in data or by making large datasets easier to understand. In this paper we present a new algorithm for seriation based on dendrograms. Dendrogram seriation algorithms rearrange the nodes in a dendrogram in order to obtain a permutation of the leaves (i.e. objects) that optimises a given criterion. Our algorithm is more flexible than currently available seriation algorithms because it allows the user to either choose from a variety of seriation criteria or to input their own criteria. This choice of seriation criteria is an important feature because different criteria are suitable for different visualisation settings. Common seriation criteria include measurements of the path length through a set of objects and measurements of anti-Robinson form in a symmetric matrix. We propose new seriation criteria called lazy path length and banded anti-Robinson form, and demonstrate their effectiveness in a variety of visualisation settings.