Toward effective many-objective optimization: Rounded-archiving. (December 2019) - Sahraei, Shahram; Asadzadeh, Masoud; Shafii, Mahyar
Abstract: Heuristic multi-objective optimization (MO) algorithms lose their efficiency and performance as the number of objectives increases, due to the so-called dominance resistance, unless they are equipped with a specialized solution archiving strategy, like epsilon ( ε −) archiving. This study introduces an alternative approach to tackle dominance resistance for solving environmental and water resources engineering problems with more than three objectives. In the proposed approach, objectives are rounded to user-defined precision levels before checking the dominance. Rounded-archiving is developed and assessed for PA-DDS and Borg MOEA and verified for AMALGAM applied to hydrologic model calibration problems with more than three objectives. Results show that rounded-archiving significantly improves the performance of MO algorithms and is at least as effective as (if not better than) the ε -archiving for solving many-objective optimization problems without the need to restructure the algorithm, which is the requirement for the implementation of the ε -archiving approach. Highlights: Rounded-archiving greatly reduces the archive size for many-objective optimization. Rounded-archiving is as effective as the epsilon-archiving for many-objective cases. Rounded archiving does not need restructuring the dominance in the algorithm. Rounded archiving handles the dominance resistance in many-objective optimization. Rounded archiving handles the deterioration in algorithms with bounded archive.