Summary

This section presents a brief summary showing some of the main proposals made in recent years concerning DOPs. We intend to give a general view over recent papers and their approach to solving DOPs using metaheuristics.

Ref. Approach Problem Metrics Year
[FMRR08] Adaptive mutation operator Royal road and deceptive functions Best of generation 2008
[RAD08] Kalman filters for future prediction Pose estimation problem Average error 2008
[KH08] Hybrid algorithm for MO optimization Route planning problem Problem dependent performance indices 2008
[HC08] SPEA-2 and robustness-enhanced R-SPEA2 Portfolio optimization problem New robustness metric 2008
[YSC08] Standard GP Financial portfolio optimization problem ROI (Problem dependent) 2008
[PCR08] Multi-populations Knapsack problem, royal road function, and deceptive function Mean best-of-generation 2008
[LFL08] Replacement strategy to keep diversity Trap functions, switching trap Best-fitness plots 2008
[YWW+08] Multi-agent hybrid EA One-max, royal road function, deceptive functions Mean best-of-generation plots 2008
[dPE08] Multi-populations DE Moving peaks Offline error 2008
[YKG08] Applies several TSP heuristics Dynamic MO TSP Best-fitness plots 2008
[TY08] Adaptive mutation operator Rastrigin functions Mean best-of-generation 2008
[KTK08] Pareto operator to predict future fronts FDA problems (Type III) Hypervolume rate 2008
[AL08] Cooperative Coevolution Moving peaks Mean best-of-generation 2008
[YT08] Hyper-selection One-max, royal road, knapsack problem Offline performance and best-of-generation plots 2008
[OBH08] Subtree deactivation for GP Best and average fitness plots 2008
Note: This site is updated regularly.

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