Article ID: | iaor20084671 |
Country: | Netherlands |
Volume: | 177 |
Issue: | 3 |
Start Page Number: | 1678 |
End Page Number: | 1702 |
Publication Date: | Mar 2007 |
Journal: | European Journal of Operational Research |
Authors: | Tamiz M., Jones D.F., Large J.W. |
Keywords: | decision theory: multiple criteria |
Multi-objective evolutionary algorithms are widely considered to have two goals: convergence towards the true Pareto front and maintaining a diverse set of solutions. The primary concern here is with the first goal of convergence, in particular when one or more variables must converge to a constant value. Using a number of well known test problems, the difficulties that are currently impeding convergence are discussed and then a new method is proposed that transforms the decision space using the geometric properties of hyper-spherical inversions to converge towards/onto the true Pareto front. Future extensions of this work and its application to multi-objective optimisation is discussed.