Divide and conquer based non-dominated sorting for parallel environment
Sumit Mishra, Sriparna Saha, Samrat Mondal · 2016
Many of the real-life problems involve simultaneous optimization of multiple objectives. In recent years there is an enormous increase in the number of multi-objective optimization problems related to different real-life domains. Evolutionary algorithms are the most popular in solving these types of problems. The non-dominating sorting is one of the steps of any multiobjective evolutionary algorithms. This is used mostly to select the non-dominated set of solutions from a given population. In the past various efficient approaches are proposed in the literature to reduce the complexity of this step. As the evolutionary algorithms inhibit parallelism in it. But not all the existing non-dominating sorting approaches have the parallelism property. So in this paper, we have proposed a new approach named as DCNS (Divide and Conquer based Non-dominating Sorting) which inhibits parallelism in it. It has been shown theoretically and empirically that the proposed approach is computationally efficient than existing state-of-the-art methods.