Publications¶

This page lists the papers behind pymocd. It gives the published paper on HP-MOCD, with two short summaries of it, and the publication status of RIMPSO, the library's two own methods, then the papers whose methods pymocd re-implements as baselines. A last section is reserved for published work that uses pymocd. For BibTeX entries and guidance on what to cite, see Citing pymocd.

pymocd's methods¶

HP-MOCD¶

Santos, G. O., Vieira, L. S., Rossetti, G., Ferreira, C. H. G., & Moreira, G. J. P. (2025). A high-performance evolutionary multiobjective community detection algorithm. Social Network Analysis and Mining, 15(1), 110. doi:10.1007/s13278-025-01519-7

This is the paper the repository README asks users of any of the library's algorithms to cite. It introduces HP-MOCD, an NSGA-II search over the intra/inter decomposition of modularity, which pymocd provides as hpmocd, hpmocd_fronts and the configurable HpMocd class. The Crossref record of the DOI lists the article under a CC BY 4.0 licence. A preprint of the same paper is available as arXiv:2506.01752; the arXiv record links to the published version.

Some of the same authors have since published two short Portuguese-language summaries of the paper. Both present HP-MOCD and refer readers to the journal paper for the full results, so cite the journal paper for the method.

Santos, G. O., Ferreira, C. H. G., & Moreira, G. J. P. (2026). HP-MOCD: Um Algoritmo Evolucionário Multiobjetivo de Alto Desempenho para Detecção de Comunidades em Redes Complexas. Revista Eletrônica de Iniciação Científica em Computação, 24, 418–424. doi:10.5753/reic.2026.8488
Santos, G. O., Vieira, L. S., Ferreira, C. H. G., & Moreira, G. J. P. (2026). HP-MOCD: Viabilizando a Detecção de Comunidades Multiobjetivo em Redes de Larga Escala. In Anais do XV Brazilian Workshop on Social Network Analysis and Mining (BraSNAM 2026), 262–268. Sociedade Brasileira de Computação. doi:10.5753/brasnam.2026.22901

The first names pymocd as the library that provides HP-MOCD and gives github.com/oliveira-sh/pymocd, now a fork of this repository, as the location of the source code. Bibliographic details follow the Crossref record of each DOI.

HP-MOCD algorithm page BibTeX

RIMPSO¶

RIMPSO, which its module README expands as RIMPSO-CD: Resolution-Indexed Memetic Particle Swarm Optimisation for Community Detection, is the library's recommended default detector, provided as rimpso, rimpso_fronts and rimpso_select. Its paper is in preparation: the repository cites it as Santos, in preparation (2026), and no DOI exists yet. Until it is published, the RIMPSO page and the module README in src/core/algorithms/rimpso/ are its full description.

Papers re-implemented in pymocd¶

pymocd re-implements the methods of the following papers as baselines. Each algorithm page gives the method's objectives, its parameters and the divergences of the port from its paper that the module README records. Bibliographic details follow the Crossref record of each DOI.

Method	Paper	Algorithm page
CDRME	Dabaghi-Zarandi, F., Afkhami, M. M., & Ashoori, M. H. (2025). Community Detection method based on Random walk and Multi objective Evolutionary algorithm in complex networks. Journal of Network and Computer Applications, 234, 104070. doi:10.1016/j.jnca.2024.104070	CDRME
MMCoMO	Zhang, L., Yang, H., Yang, S., & Zhang, X. (2023). A Macro-Micro Population-Based Co-Evolutionary Multi-Objective Algorithm for Community Detection in Complex Networks [Research Frontier]. IEEE Computational Intelligence Magazine, 18(3), 69–86. doi:10.1109/MCI.2023.3277773	MMCoMO
NSGA-III-CCM, NSGA-III-KRM	Shaik, T., Ravi, V., & Deb, K. (2021). Evolutionary Multi-Objective Optimization Algorithm for Community Detection in Complex Social Networks. SN Computer Science, 2(1), 1. doi:10.1007/s42979-020-00382-x	NSGA-III-CCM, NSGA-III-KRM
GDPSO	Cai, Q., Gong, M., Ma, L., Ruan, S., Yuan, F., & Jiao, L. (2015). Greedy discrete particle swarm optimization for large-scale social network clustering. Information Sciences, 316, 503–516. doi:10.1016/j.ins.2014.09.041	GDPSO
Shi-MOCD (MOCD-Q, MOCD-D)	Shi, C., Yan, Z., Cai, Y., & Wu, B. (2012). Multi-objective community detection in complex networks. Applied Soft Computing, 12(2), 850–859. doi:10.1016/j.asoc.2011.10.005	Shi-MOCD
MOGA-Net	Pizzuti, C. (2012). A Multiobjective Genetic Algorithm to Find Communities in Complex Networks. IEEE Transactions on Evolutionary Computation, 16(3), 418–430. doi:10.1109/TEVC.2011.2161090	MOGA-Net

The Shaik et al. paper was published online in November 2020 and appeared in volume 2 (2021) as article 1. For MOGA-Net, the module README also draws on Pizzuti's earlier conference paper, "A Multi-objective Genetic Algorithm for Community Detection in Networks", 21st IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2009, pp. 379–386 (doi:10.1109/ICTAI.2009.58), which defines the operators.

HP-MOCD's objective pair follows the formulation of Shi, Zhong, Yan, Cai & Wu (2010), "A multi-objective approach for community detection in complex network", IEEE Congress on Evolutionary Computation, pp. 1–8 (doi:10.1109/CEC.2010.5585987), which is the Shi et al. paper the HP-MOCD paper cites. The module README takes the equations from Shi et al.'s later journal paper, Shi et al. (2012), Eqs. 3.5 and 3.6, which is the paper Shi-MOCD ports. The HP-MOCD page lists the works it builds on.

Publications using pymocd¶

No published work by other authors that uses pymocd has been confirmed yet. Of the works found that cite the HP-MOCD paper, those whose full text could be read cite it without using pymocd.

If you have published work that uses pymocd, please let us know by opening an issue on GitHub with the full citation and its DOI, so that it can be listed here.