简介和使用方法

PlatEMO是基于Matlab的一款拥有可视化界面的多目标优化算法平台。

• 下载文件，下载链接：https://github.com/BIMK/PlatEMO

• 文件下载完成后，解压文件

• 使用Matlab运行main.m文件，文件所在位置：..\PlatEMO-master\PlatEMO\main.m

• 运行后的界面如下所示：

  

左侧的"Algorithm"是选择算法，"Problem"是需要解决的问题，"RUN"   是运行。中间的是图像趋于，会展示算法的优化过程。

可以解决的问题

目前，根据官方的文件给出的可以解决的问题即参考文献如下：(文献链接事笔者自己找到的网上资料，链接部分可能已经失效。在www.lolplayer.club的“分享经验”第20篇文章中可以直接点击获取文献。)

1. ZDT：由：Zitzler、Deb和Thiele提出基准的MOP  文献：E. Zitzler, K. Deb, and L. Thiele, Comparison of multiobjective evolutionary algorithms: Empirical results, Evolutionary computation, 2000, 8(2): 173-195.   网址：https://dl.acm.org/doi/10.1162/106365600568202

2. WFG：由Walking Fish Group提出基准的MOP   文献：S. Huband, P. Hingston, L. Barone, and L. While, A review of multiobjective test problems and a scalable test problem toolkit, IEEE Transactions on Evolutionary Computation, 2006, 10(5): 477-506.  网址：https://www.researchgate.net/profile/Philip_Hingston/publication/3418888_A_review_of_multiobjective_test_problems_and_a_scalable_test_problem_toolkit/links/02e7e5167f703d8e46000000/A-review-of-multiobjective-test-problems-and-a-scalable-test-problem-toolkit.pdf

3. VNT：由Viennet提出基准的MOP    文献：R. Viennet, C. Fonteix, and I. Marc, Multicriteria optimization using a genetic algorithm for determining a Pareto set, International Journal of Systems Science, 1996, 27(2): 255-260.   网站：https://www.researchgate.net/publication/242928480_Multicriteria_optimization_using_a_genetic_algorithm_for_determining_a_Pareto_set

4. UF：无约束基准MOP   文献：Q. Zhang, A. Zhou, S. Zhao, P. N. Suganthan, W. Liu, and S. Tiwari, Multiobjective optimization test instances for the CEC 2009 special session and competition, School of CS & EE, University of Essex, Working Report CES-487, 2009   网站：https://www.researchgate.net/profile/Ponnuthurai_Suganthan/publication/265432807_Multiobjective_optimization_Test_Instances_for_the_CEC_2009_Special_Session_and_Competition/links/54b7d9940cf2c27adc473433.pdf

5. TREE：时变比误差估计问题   文献：C. He, R. Cheng, C. Zhang, Y. Tian, Q. Chen, and X. Yao, Evolutionary large-scale multiobjective optimization for ratio error estimation of voltage transformers, IEEE Transactions on Evolutionary Computation, 2020.    网站：https://ieeexplore.ieee.org/document/8962275

6. SMOP：具有稀疏帕累托最优解的MOP  文献：Y. Tian, X. Zhang, C. Wang, and Y. Jin, An evolutionary algorithm for large-scale sparse multi-objective optimization problems, IEEE Transactions on Evolutionary Computation, 2019.   网址：https://ieeexplore.ieee.org/document/8720021

7. MW：Ma和Wang提出的优约束的MOP  文献：Z. Ma and Y. Wang, Evolutionary constrained multiobjective optimization: Test suite construction and performance comparisons. IEEE Transactions on Evolutionary Computation, 2019.     网址：https://ieeexplore.ieee.org/document/8632683

8. MOPs in RM-MEDA：基于正则模型多目标分布估计算法的MOP 文献：Q. Zhang, A. Zhou, and Y. Jin, RM-MEDA: A regularity model-based multiobjective estimation of distribution algorithm, IEEE Transactions on Evolutionary Computation, 2008, 12(1): 41-63.   网址：https://ieeexplore.ieee.org/document/4358761?arnumber=4358761

9. MOPs in MOEA-D-M2M：基于分解的多目标优化进化算法的MOP问题  文献：H. Liu, F. Gu, and Q. Zhang, Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems, IEEE Transactions on Evolutionary Computation, 2014, 18(3): 450-455.   网址：https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6595549

10. MOPs in MOEA-D-DE：基于差分分解的多目标优化算法的MOP问题   文献：H. Liu, F. Gu, and Q. Zhang, Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems, IEEE Transactions on Evolutionary Computation, 2014, 18(3): 450-455.   网址：https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6595549

11. MOPs in IM-MOEA：基于高斯过程逆建模的多目标进化算法的MOP问题  文献：R. Cheng, Y. Jin, K. Narukawa, and B. Sendhoff, A multiobjective evolutionary algorithm using Gaussian process-based inverse modeling, IEEE Transactions on Evolutionary Computation, 2015, 19(6): 838-856.    网址：https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7018980

12. MaF：多目标优化的复杂智能系统    文献：R. Cheng, M. Li, Y. Tian, X. Zhang, S. Yang, Y. Jin, and X. Yao, A benchmark test suite for evolutionary many-objective optimization, Complex & Intelligent Systems, 2017, 3(1): 67-81.   网址：https://www.researchgate.net/publication/315446832_A_benchmark_test_suite_for_evolutionary_many-objective_optimization

13. LSMOP：大规模基准的MOP问题   文献：R. Cheng, Y. Jin, and M. Olhofer, Test problems for large-scale multiobjective and many-objective optimization, IEEE Transactions on Cybernetics, 2017, 47(12): 4108-4121.  网址：https://www.semanticscholar.org/paper/Test-Problems-for-Large-Scale-Multiobjective-and-Cheng-Jin/11f96ea3e2a645eddd869579f36615a2e87783c4?p2df

14. LIRCMOP：具有较大不可行区域的约束基准MOP   文献：Z. Fan, W. Li, X. Cai, H. Huang, Y. Fang, Y. You, J. Mo, C. Wei, and E. Goodman, An improved epsilon constraint-handling method in MOEA/D for CMOPs with large infeasible regions, Soft Computing, 2019.   网址：https://arxiv.org/pdf/1707.08767.pdf

15. IMOP：不规则Pareto前沿的MOP   文献：Y. Tian, R. Cheng, X. Zhang, M. Li, and Y. Jin, Diversity assessment of multi-objective evolutionary algorithms: Performance metric and benchmark problems, IEEE Computational Intelligence Magazine, 2019.    网址：https://ieeexplore.ieee.org/document/8765427
 
16. DTILZ：由Deb, Thiele, Laumanns, and Zitzler提出的MOP问题  文献：K. Deb, L. Thiele, M. Laumanns, and E. Zitzler, Scalable test problems for evolutionary multiobjective optimization, Evolutionary multiobjective Optimization. Theoretical Advances and Applications, 2005, 105-145.  网站：https://www.semanticscholar.org/paper/Scalable-Test-Problems-for-Evolutionary-Deb-Thiele/277706e9ea2a0aea2d7433089fee5e163205dc4a?p2df

17. DOC：决策和目标空间的约束的MOP  文献：Z. Liu and Y. Wang, Handling constrained multiobjective optimization problems with constraints in both the decision and objective spaces. IEEE Transactions on Evolutionary Computation, 2019.   网址：https://www.researchgate.net/publication/330580491_Handling_Constrained_Multiobjective_Optimization_Problems_With_Constraints_in_Both_the_Decision_and_Objective_Spaces

18. MLDMP：多线距离最小化问题   文献：M. Li, C. Grosan, S. Yang, X. Liu, and X. Yao, Multiline distance minimization: A visualized many-objective test problem suite, IEEE Transactions on Evolutionary Computation, 2018, 22(1): 61-78.   网址：https://www.dora.dmu.ac.uk/bitstream/handle/2086/13238/IEEETEVC17-All.pdf?sequence=3&isAllowed=y

19. DAS-CMOP：困难-可调节和可伸缩的约束基准MOP  文献：Z. Fan, W. Li, X. Cai, H. Li, C. Wei, Q. Zhang, K. Deb, and E. Goodman, Difficulty adjustable and scalable constrained multi-objective test problem toolkit, Evolutionary Computation, 2019.   网址：https://www.semanticscholar.org/paper/Difficulty-Adjustable-and-Scalable-Constrained-Test-Fan-Li/5566c8051d467419199b78aa29b1898713e61304?p2df

20. MOKP：多目标背包问题   文献：E. Zitzler and L. Thiele, Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach, IEEE Transactions on Evolutionary Computation, 1999, 3(4): 257-271.   网站：  https://www.researchgate.net/publication/2240388_Thiele_L_Multiobjective_Evolutionary_Algorithms_A_Comparative_Case_Study_and_the_Strength_Pareto_Approach_IEEE_Trans_on_Evolutionary_Computation_3_257-271

MONRP：多目标Next Release问题  文献：Y. Zhang, M. Harman, and S. A. Mansouri, The multi-objective next release problem, Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, 2007, 1129-1137.   网站：http://www0.cs.ucl.ac.uk/staff/M.Harman/gecco07yz.pdf
     
 MOTSP：多目标旅行商问题        文献：D. Corne and J. Knowles, Techniques for highly multiobjective optimisation: some nondominated points are better than others, Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, 2007, 773-780.   网站：https://www.researchgate.net/profile/Joshua_Knowles/publication/45868377_Techniques_for_Highly_Multiobjective_Optimisation_Some_Nondominated_Points_are_Better_than_Others/links/0912f509274ba30f19000000/Techniques-for-Highly-Multiobjective-Optimisation-Some-Nondominated-Points-are-Better-than-Others.pdf

mQAP：多目标二次分配问题      文献：J. Knowles and D. Corne, Instance generators and test suites for the multiobjective quadratic assignment problem, Proceedings of the International Conference on Evolutionary Multi-Criterion Optimization, 2003, 295-310.    网站：https://www.mendeley.com/catalogue/d18d5b9a-52b6-3209-9552-b6d48311e066/
21. CF：约束基准MOP  文献：Q. Zhang, A. Zhou, S. Zhao, P. N. Suganthan, W. Liu, and S. Tiwari, Multiobjective optimization test instances for the CEC 2009 special session and competition, School of CS & EE, University of Essex, Working Report CES-487, 2009.    网站：https://www.researchgate.net/profile/Ponnuthurai_Suganthan/publication/265432807_Multiobjective_optimization_Test_Instances_for_the_CEC_2009_Special_Session_and_Competition/links/54b7d9940cf2c27adc473433.pdf
 
22. BT：基于偏差特征的MOP  文献：H. Li, Q. Zhang, and J. Deng, Biased multiobjective optimization and decomposition algorithm, IEEE Transactions on Cybernetics, 2017, 47(1): 52-66.
网站：http://repository.essex.ac.uk/18553/1/07397980.pdf

参考资料：
Ye Tian, Ran Cheng, Xingyi Zhang, and Yaochu Jin, “PlatEMO: A MATLAB platform for evolutionary multi‐objective optimization [educational forum],” IEEE Computational Intelligence Magazine, 2017, 12(4): 73‐87.

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