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Diversity maintenance of solutions is a crucial part in multi-objective optimization. However, most of existing studies show a good distribution with a large computational load or a comparative bad distribution quickly. In this paper, a method for pruning a set of non-dominated solutions using a spanning tree is proposed. This approach defines a density estimation metric - spanning tree crowding distance...
Fitness assignment and external population maintenance are two important parts of mufti-objective evolutionary algorithms. In this paper, we propose a new MOEA which uses the information of minimum spanning tree to assign fitness and maintain the external population. Moreover, a Minimum Spanning Tree Crowding Distance (MSTCD) is defined to estimate the density of solutions. From an extensive comparative...
Uniformity assessment of approximations of the Pareto-optimal set is an important issue in comparing the performance of multi-objective evolutionary algorithms. Although a number of performance metrics existed, many are applicable to low objective problems (2-3 objectives). In addition, most of the existed metrics are only applied to the final non-dominated set. In this paper, we suggest a running...
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