The mcMST package provides a set of algorithms to approximate the Pareto-optimal set/front of multi-criteria minimum spanning tree (mcMST) problems.
Currently, the following algorithms are included:
A multi-criteria version of Prim's algorithm for the single-objective MST (see ).
Evolutionary multi-objective algorithm operating on the Pruefer-encoding as proposed by Zhou and Gen .
Evolutionary multi-objective algorithm operating on a direct edge list encoding. This algorithm applies a sub-tree based mutation operator as proposed by Bossek and Grimme .
A simple method to enumerate all Pareto-optimal solutions of a given combinatorial problem. This method is not limited to mcMST problems.
 Knowles, J. D., and Corne, D. W. 2001. A Comparison of Encodings and Algorithms for Multiobjective Minimum Spanning Tree Problems. In Proceedings of the 2001 Congress on Evolutionary Computation (Ieee Cat. No.01TH8546), 1:544–51 vol. 1. doi:10.1109/CEC.2001.934439.
 Zhou, G., and Gen, M. 1999. Genetic Algorithm Approach on Multi-Criteria Minimum Spanning Tree Problem. European Journal of Operational Research 114 (1): 141–52. doi:https://doi.org/10.1016/S0377- 2217(98)00016-2.
 Bossek, J., and Grimme, C. 2017. A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem. In Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence. (accepted)
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