Multiobjective evolutionary algorithms : A survey of the state of the art. Swarm and Evolutionary Computation

Zhou, A., Qu, B., Li, H., Zhao, S., & Nagaratnam, P. (2011). Multiobjective evolutionary algorithms : A survey of the state of the art. Swarm and Evolutionary Computation, 1(1), 32–49. doi:10.1016/j.swevo.2011.03.00
多目的最適化のsurvey論文。
非常に広く調査している。必読。

Multiobjective evolutionary algorithms: A survey of the state of the art
1. Introduction
2. Advances in MOEA design
2.1 Algorithm framworks
2.1.1. An MOEA based on decomposion: MOEA/D
2.1.2 MOEAs based on preference
2.1.3 Indicator based MOEAs
2.1.4 Hybrid MOEAs
2.1.5 Memtic MOEAs
2.1.6 MOEAs based on coevolution
2.2 Selection and population updating
2.2.1 Complete orders over individuals
2.2.2 Complete orders over populations
2.3 Reproduction
2.3.1 DE-Based Approaches
2.3.2 Immune-based appraches
2.3.3 PSO-based approaces
2.3.4 Prbabilistic model-based appraches
2.3.5 SA-based approaches
2.3.6 Other approaces
2.4 Other issues
2.4.1 Theoretical studies of MOEAs
2.4.2 Adaptation
3. MOEAs for complicated problems
3.1 Constraint handling in MOEAs
3.2 MOEAs as constrint handling methods
3.3 MOEAs and multimodal problems
3.4 MOEAs for many-objective problems
3.5 Compuationally expensive multiobjective optimization
3.6 Dynamic multiobjective optimizaiton
3.7 Noisy multiobjective optimization
3.8 MOEAs for combinatorial and discrete problems
4. Benchmark problems and performance measures
4.1 Benchmark problems
4.2 Performance measures
5. Applications
6. Conclusions and future directions