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Multi-objective optimisation yields an estimated Pareto front of mutually non-dominating solutions, but with more than three objectives understanding the relationships between solutions is challenging. Natural solutions to use as <i>landmarks</i> are those lying near to the edges of the mutually non-dominating set. We propose four definitions of <i>edge(More)
Interpreting individuals described by a set of criteria can be a difficult task when the number of criteria is large. Such individuals can be ranked, for instance in terms of their average rank across criteria as well as by each distinct criterion. We therefore investigate criteria selection methods which aim to preserve the average rank of individuals but(More)
Optimisation problems often comprise a large set of objectives, and visualising the set of solutions to a problem can help with understanding them, assisting a decision maker. If the set of objectives is larger than three, visualising solutions to the problem is a difficult task. Techniques for visualising high-dimensional data are often difficult to(More)
Hyper-heuristics have been used widely to solve optimisation problems, often single-objective and discrete in nature. Herein, we extend a recently-proposed selection hyper-heuristic to the multi-objective domain and with it optimise continuous problems. The MOSSHH algorithm operates as a hidden Markov model, using transition probabilities to determine which(More)
Serum and glucocorticoid-inducible kinase 1 (SGK1) is a protein kinase that contributes to the hormonal control of renal Na(+) retention by regulating the abundance of epithelial Na(+) channels (ENaC) at the apical surface of the principal cells of the cortical collecting duct (CCD). Although glucocorticoids and insulin stimulate Na(+) transport by(More)