A New Decomposition Many-Objective Evolutionary Algorithm Based on - Efficiency Order Dominance

  • Guo XiaofangEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 81)


Decomposition-based evolutionary algorithms are promising for handling many objective optimization problems with more than three objectives in the past decade. In the proposed algorithm, we develop a new dominance relation based on - efficiency order dominance (MOEA/D-\( \upvarepsilon{\text{EOD}} \)) in each sub-problem to realize the selection and update of the individuals. Besides, a dynamic adaptive weight vector generation method is proposed, which is able to dynamically adjust the weight vector setting according to the current distribution of the non-dominated solution set. The proposed algorithm has been tested extensively on six widely used benchmark problems, and an extensive comparison indicates that the proposed algorithm offers competitive advantages in convergence and diversity.


Decomposition \( \upvarepsilon \)-dominance efficiency order rank Many-objective 



This work was supported by the special scientific research project fund of education department of Shaanxi Province (16JK1381) and the National Natural Science Foundations of China (No. 61472297). The authors would like to thank the anonymous reviewers for their valuable comments and suggestions.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.School of ScienceXi’an Technological UniversityXi’anChina

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