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M.L.: Adaptive Diversity Maintenance and Convergence Guarantee in Multiobjective Evolutionary Algorithms (2003)
| Content Provider | CiteSeerX |
|---|---|
| Author | Jin, Huidong Wong, Man Leung |
| Description | In: Proceedings of the 2003 Congress on Evolutionary Computation (CEC 2003 |
| Abstract | Abstract- The trade-off between obtaining a well-converged and well-distributed set of Pareto optimal solutions, and obtaining them efficiently and automat-ically is an important issue in multi-objective evo-lutionary algorithms (MOEAs). Many studies have depicted different approaches that evolutionary algo-rithms can progress towards the Pareto optimal set with a wide-spread distribution of solutions. However, most mathematically convergent MOEAs desire certain prior knowledge of the solution space in order to ef-ficiently maintain widespread solutions. In this pa-per, we propose, based on the E-dominance concept, an Adaptive Rectangle Archiving (ARA) strategy that over-comes this practically crucial problem. The MOEAs with this archiving technique provably converge to well-distributed Pareto sets without a priori. ARA comple-ments the existing archiving techniques, and is useful to both researchers and practitioners. 1 |
| File Format | |
| Publisher Date | 2003-01-01 |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Proceeding Article |
