Multi-level Ranking for Constrained Multi-objective Evolutionary Optimisation

  • Philip Hingston
  • Luigi Barone
  • Simon Huband
  • Lyndon While
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)


In real-world optimisation problems, feasibility of solutions is invariably an essential requirement. A natural way to deal with feasibility is to cast it as an additional objective in a multi-objective optimisation setting. In this paper, we consider two possible ways to do this, using a multi-level scheme for ranking solutions. One strategy considers feasibility first, before considering objective values, while the other reverses this ordering. The first strategy has been explored before, while the second has not. Experiments show that the second strategy can be much more successful on some difficult problems.


Feasible Region Benchmark Problem Infeasible Solution Ranking Scheme Pareto Dominance 
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

  • Philip Hingston
    • 1
  • Luigi Barone
    • 2
  • Simon Huband
    • 1
  • Lyndon While
    • 2
  1. 1.Edith Cowan UniversityMt LawleyAustralia
  2. 2.The University of Western AustraliaCrawleyAustralia

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