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A Fast Incremental BSP Tree Archive for Non-dominated Points

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10173)

Abstract

Maintaining an archive of all non-dominated points is a standard task in multi-objective optimization. Sometimes it is sufficient to store all evaluated points and to obtain the non-dominated subset in a post-processing step. Alternatively the non-dominated set can be updated on the fly. While keeping track of many non-dominated points efficiently is easy for two objectives, we propose an efficient algorithm based on a binary space partitioning (BSP) tree for the general case of three or more objectives. Our analysis and our empirical results demonstrate the superiority of the method over the brute-force baseline method, as well as graceful scaling to large numbers of objectives.

Keywords

Pareto Front Candidate Point Objective Vector Space Cell Covariance Matrix Adaptation Evolution Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute for Neural ComputationRuhr-University BochumBochumGermany

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