Coverage for moptipy / algorithms / so / ffa / __init__.py: 100%

1""" 

2Algorithms and modules based on Frequency Fitness Assignment (FFA). 

3 

4Frequency Fitness Assignment (FFA) is an algorithm plugin developed by the 

5team behind `moptipy`. FFA is suitable only for problems where the number 

6of different objective values is not too high. On such problems, which are 

7often discrete or combinatorial, it often can improve the result quality 

8that the optimization algorithms can reach, at the expense of requiring a 

9larger runtime. 

10 

111. Thomas Weise, Zhize Wu, Xinlu Li, and Yan Chen. Frequency Fitness 

12 Assignment: Making Optimization Algorithms Invariant under Bijective 

13 Transformations of the Objective Function Value. *IEEE Transactions on 

14 Evolutionary Computation* 25(2):307-319. April 2021. Preprint available at 

15 arXiv:2001.01416v5 [cs.NE] 15 Oct 2020. 

16 https://dx.doi.org/10.1109/TEVC.2020.3032090 

172. Thomas Weise, Zhize Wu, Xinlu Li, Yan Chen, and Jörg Lässig. Frequency 

18 Fitness Assignment: Optimization without Bias for Good Solutions can be 

19 Efficient. *IEEE Transactions on Evolutionary Computation (TEVC)*. 

20 27(4):980-992. August 2023. 

21 doi: https://doi.org/10.1109/TEVC.2022.3191698 

223. Thomas Weise, Mingxu Wan, Ke Tang, Pu Wang, Alexandre Devert, and Xin 

23 Yao. Frequency Fitness Assignment. *IEEE Transactions on Evolutionary 

24 Computation (IEEE-EC),* 18(2):226-243, April 2014. 

25 https://dx.doi.org/10.1109/TEVC.2013.2251885 

264. Thomas Weise, Yan Chen, Xinlu Li, and Zhize Wu. Selecting a diverse set of 

27 benchmark instances from a tunable model problem for black-box discrete 

28 optimization algorithms. *Applied Soft Computing Journal (ASOC),* 

29 92:106269, June 2020. https://dx.doi.org/10.1016/j.asoc.2020.106269 

305. Thomas Weise, Xinlu Li, Yan Chen, and Zhize Wu. Solving Job Shop Scheduling 

31 Problems Without Using a Bias for Good Solutions. In *Genetic and 

32 Evolutionary Computation Conference Companion (GECCO'21 Companion),* 

33 July 10-14, 2021, Lille, France. ACM, New York, NY, USA. 

34 ISBN 978-1-4503-8351-6. https://dx.doi.org/10.1145/3449726.3463124 

356. Thomas Weise, Mingxu Wan, Ke Tang, and Xin Yao. Evolving Exact Integer 

36 Algorithms with Genetic Programming. In *Proceedings of the IEEE Congress 

37 on Evolutionary Computation (CEC'14), Proceedings of the 2014 World 

38 Congress on Computational Intelligence (WCCI'14),* pages 1816-1823, 

39 July 6-11, 2014, Beijing, China. Los Alamitos, CA, USA: IEEE Computer 

40 Society Press. ISBN: 978-1-4799-1488-3. 

41 https://dx.doi.org/10.1109/CEC.2014.6900292 

427. Tianyu Liang, Zhize Wu, Jörg Lässig, Daan van den Berg, Sarah Louise 

43 Thomson, and Thomas Weise. Addressing the Traveling Salesperson Problem 

44 with Frequency Fitness Assignment and Hybrid Algorithms. *Soft Computing.* 

45 2024. https://dx.doi.org/10.1007/s00500-024-09718-8 

46"""