A Fast and Effective Method for Pruning of Non-dominated Solutions in Many-Objective Problems

  • Saku Kukkonen
  • Kalyanmoy Deb
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)


Diversity maintenance of solutions is an essential part in multi-objective optimization. Existing techniques are suboptimal either in the sense of obtained distribution or execution time. This paper proposes an effective and relatively fast method for pruning a set of non-dominated solutions. The proposed method is based on a crowding estimation technique using nearest neighbors of solutions in Euclidean sense, and a technique for finding these nearest neighbors quickly. The method is experimentally evaluated, and results indicate a good trade-off between the obtained distribution and execution time. Distribution is good also in many-objective problems, when number of objectives is more than two.


Multiobjective Optimization Vector Quantization Pruning Method Strength Pareto Evolutionary Algorithm Crowd Distance 
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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© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Saku Kukkonen
    • 1
  • Kalyanmoy Deb
    • 2
  1. 1.Department of Information TechnologyLappeenranta University of TechnologyLappeenrantaFinland
  2. 2.Kanpur Genetic Algorithms Laboratory (KanGAL)Indian Institute of Technology KanpurKanpurIndia

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