An Improved Version of Volume Dominance for Multi-Objective Optimisation

  • Khoi Le
  • Dario Landa-Silva
  • Hui Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5467)


This paper proposes an improved version of volume dominance to assign fitness to solutions in Pareto-based multi-objective optimisation. The impact of this revised volume dominance on the performance of multi-objective evolutionary algorithms is investigated by incorporating it into three approaches, namely SEAMO2, SPEA2 and NSGA2 to solve instances of the 2-, 3- and 4- objective knapsack problem. The improved volume dominance is compared to its previous version and also to the conventional Pareto dominance. It is shown that the proposed improved volume dominance helps the three algorithms to obtain better non-dominated fronts than those obtained when the two other forms of dominance are used.


Pareto Front Nondominated Solution Pareto Dominance Multiobjective Evolutionary Algorithm True Pareto Front 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Khoi Le
    • 1
  • Dario Landa-Silva
    • 1
  • Hui Li
    • 1
  1. 1.Automated Scheduling, Optimisation and Planning Research Group School of Computer ScienceThe University of NottinghamUK

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