trees are binary, split fit is co-Pareto on components (Wilkinson et al., 2005a). When input trees have polytomies, an optimal split fit supertree could include arbitrary resolutions that do not contradict any displayed splits. In that case, split fit can fail to be co-Pareto (but not sub-Pareto) on components. In contrast, the corresponding strict consensus, the split fit* supertree, suppresse...

MOEA/D is a novel and successful Multi-Objective Evolutionary Algorithms(MOEA) which utilizes the idea of problem decomposition to tackle the complexity from multiple objectives. It shows better performance than most nowadays mainstream MOEA methods in various test problems, especially on the quality of solution's distribution in the Pareto set. This paper aims to bring the strength of metamode...

In this paper, multi-objective optimization is applied to determine the parameters for a k-nearest neighbours classifier that has been used in the diagnosis of Paroxysmal Atrial Fibrillation (PAF), in order to get optimal combinations of classification rate, sensibility and specificity. We have considered three different evolutionary algorithms for implementing the multiobjective optimization o...

In this research work, an experimental evaluation was conducted to explore the fretting fatigue life of multilayer Cr–CrN-coated AL7075-T6 alloy specimens with higher adhesion strength to substrate as the coating adhesion strength is one of the most critical issues in magnetron sputtering technique. Physical vapor deposition (PVD) magnetron sputtering technique was used for coating purpose, and...

Local Indicators of Spatial Aggregation (LISA) can be used as objectives in a multicriteria framework when highly autocorrelated areas (hot-spots) must be identified and geographically located in complex areas. To do so, a Multi-Objective Evolutionary Algorithm (MOEA) based on SPEA2 (Strength Pareto Evolutionary Algorithm v.2) has been designed to evaluate three different fitness functions (fin...

This paper presents a method, based on the Strength Pareto Evolutionary Algorithm (SPEA), designed to solve multi-objective convex integer optimization problems. The proposed method has the aim to overcome some shortcomings of SPEA, as noted in [2]. An interaction phase with the Decision Maker (DM) is also included in the method, so that the search process can be quickly directed to the part of...