Update README.md

README.md

@@ -36,6 +36,7 @@ This respository aims to maintain a list of useful relevant papers and open sour
 |Benchmark|Paper|Original Repository|About|
 |:-:|:-:|:-:|:-:|
 |MetaBox|Ma, Zeyuan, et al. "[**MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning**](https://neurips.cc/virtual/2023/oral/73737)." Advances in Neural Information Processing Systems 36 (2023).|[GMC-DRL/MetaBox]( https://github.com/GMC-DRL/MetaBox)|[PDF](Benchmarks/MetaBox/MetaBox%20A%20Benchmark%20Platform%20for%20Meta-Black-Box%20Optimization%20with%20Reinforcement%20Learning.pdf)  [BibTex](Benchmarks/MetaBox/BibTex)|
+|MA-BBOB|Vermetten, Diederick, et al. "[**MA-BBOB: A Problem Generator for Black-Box Optimization Using Affine Combinations and Shifts**](https://arxiv.org/abs/2312.11083)." arXiv preprint arXiv:2312.11083 (2023).|[Dvermetten/Many-affine-BBOB](https://github.com/Dvermetten/Many-affine-BBOB)|[PDF](Benchmarks/MA-BBOB/MA-BBOB%20A%20Problem%20Generator%20for%20Black-Box%20Optimization%20Using%20Affine%20Combinations%20and%20Shifts.pdf)  [BibTex](Benchmarks/MA-BBOB/BibTex)|
 |COCO|Hansen, Nikolaus, et al. "[**COCO: A platform for comparing continuous optimizers in a black-box setting**](https://www.tandfonline.com/doi/abs/10.1080/10556788.2020.1808977)." Optimization Methods and Software 36.1 (2021): 114-144.|[numbbo/coco](https://github.com/numbbo/coco)|[PDF](Benchmarks/COCO/COCO%20A%20platform%20for%20comparing%20continuous%20optimizers%20in%20a%20black-box%20setting.pdf)  [BibTex](Benchmarks/COCO/BibTex)|
 |IOHprofiler (IOHexperimenter)|Doerr, Carola, et al. "[**IOHprofiler: A benchmarking and profiling tool for iterative optimization heuristics**](https://arxiv.org/abs/1810.05281)." arXiv preprint arXiv:1810.05281 (2018).<br>de Nobel, Jacob, et al. "[**Iohexperimenter: Benchmarking platform for iterative optimization heuristics**](https://direct.mit.edu/evco/article/doi/10.1162/evco_a_00342/116949)." Evolutionary Computation (2023): 1-6.|[IOHprofiler/<br>IOHexperimenter](https://github.com/IOHprofiler/IOHexperimenter)|[PDF](Benchmarks/IOHprofiler/)  [BibTex](Benchmarks/IOHprofiler/BibTex)|
 |AClib|Hutter, Frank, et al. "[**AClib: A benchmark library for algorithm configuration**](https://link.springer.com/chapter/10.1007/978-3-319-09584-4_4)." Learning and Intelligent Optimization: 8th International Conference. Revised Selected Papers 8. Springer International Publishing, 2014.|[aclib.net](https://www.aclib.net/)|[PDF](Benchmarks/AClib/AClib%20A%20benchmark%20library%20for%20algorithm%20configuration.pdf)  [BibTex](Benchmarks/AClib/BibTex)|
@@ -144,6 +145,7 @@ This respository aims to maintain a list of useful relevant papers and open sour
 
 |Algorithm|Paper|Original Repository|About|
 |:-:|:-:|:-:|:-:|
+|AMCDE|Ye, Chenxi, et al. "[**Differential evolution with alternation between steady monopoly and transient competition of mutation strategies**](https://www.sciencedirect.com/science/article/pii/S2210650223001761)." Swarm and Evolutionary Computation 83 (2023): 101403.|-|[PDF](Classic%20BBO/Differential%20Evolution/AMCDE/Differential%20evolution%20with%20alternation%20between%20steady%20monopoly%20and%20transient%20competition%20of%20mutation%20strategies.pdf)  [BibTex](Classic%20BBO/Differential%20Evolution/AMCDE/BibTex)|
 |NL-SHADE-LBC|Stanovov, Vladimir, Akhmedova, Shakhnaz and Semenkin, Eugene "[**NL-SHADE-LBC algorithm with linear parameter adaptation bias change for CEC 2022 Numerical Optimization**](https://ieeexplore.ieee.org/abstract/document/9870295/)." 2022 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2022.|-|[PDF](Classic%20BBO/Differential%20Evolution/NL-SHADE-LBC/NL-SHADE-LBC%20algorithm%20with%20linear%20parameter%20adaptation%20bias%20change%20for%20CEC%202022%20Numerical%20Optimization.pdf)  [BibTex](Classic%20BBO/Differential%20Evolution/NL-SHADE-LBC/BibTex)|
 |MadDE|Biswas, Subhodip, et al. "[**Improving differential evolution through Bayesian hyperparameter optimization**](https://ieeexplore.ieee.org/abstract/document/9504792/)." 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2021.|[subhodipbiswas/<br>MadDE](https://github.com/subhodipbiswas/MadDE)|[PDF](Classic%20BBO/Differential%20Evolution/MadDE/Improving%20differential%20evolution%20through%20Bayesian%20hyperparameter%20optimization.pdf)  [BibTex](Classic%20BBO/Differential%20Evolution/MadDE/BibTex)|
 |jDE21|Brest, Janez, Mirjam Sepesy Maučec, and Borko Bošković. "[**Self-adaptive differential evolution algorithm with population size reduction for single objective bound-constrained optimization: Algorithm j21**](https://ieeexplore.ieee.org/abstract/document/9504782/)." 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2021.|-|[PDF](Classic%20BBO/Differential%20Evolution/jDE21/Self-adaptive%20differential%20evolution%20algorithm%20with%20population%20size%20reduction%20for%20single%20objective%20bound-constrained%20optimization%20Algorithm%20j21.pdf)  [BibTex](Classic%20BBO/Differential%20Evolution/jDE21/BibTex)|