Multi-objective optimisation of split-plot designs

Modern experiments allow scientists to tackle scientific problems of increasing complexity. Often are characterised by factors that have levels which harder set than others. A possible solution is the use a split-plot design. Many solutions available in literature find optimal designs focus solely on optimising single criterion. Multi-criteria approaches been developed overcome limitations one-objective optimisation, however they mainly estimating precision fixed factor effects, ignoring variance component estimation. The Multi-Stratum Two-Phase Local Search (MS-TPLS) algorithm for multi-objective optimisation extended, order ensure pure-error estimation components. proposed applied two motivating and final Pareto front related compared with other from relevant literature. Experimental results show obtained represent good candidate based different objectives.