Referensi
- CMSC 451: Maximum Bipartite Matching, https://www.cs.cmu.edu/~ckingsf/bioinfo-lectures/matching.pdf
- A resource sharing (sharing platform) scheme on online taxi services, https://www.matec-conferences.org/articles/matecconf/pdf/2019/19/matecconf_concern2018_03010.pdf
- Get started with R igraph, https://igraph.org/r/
- Network Analysis and Visualization with R and igraph, https://kateto.net/netscix2016.html
- Practical statistical network analysis (with R and igraph), http://statmath.wu.ac.at/research/friday/resources_WS0708_SS08/igraph.pdf
- maxmatching: Maximum Matching for General Weighted Graph, https://rdrr.io/cran/maxmatching/
- Hungarian Method, http://opensourc.es/blog/hungarian-method
- The Hungarian Method, https://www-m9.ma.tum.de/graph-algorithms/matchings-hungarian-method/index_en.html
- Optimiz(s)ation Algorithms, https://www.comp.nus.edu.sg/~stevenha/cs4234/lectures/08.Matching.pdf
- The Munkres Assignment Algorithm (Hungarian Algorithm), https://www.youtube.com/watch?v=cQ5MsiGaDY8
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Referensi
- GeoDa is a free and open source software tool that serves as an introduction to spatial data analysis. It is designed to facilitate new insights from data analysis by exploring and modeling spatial patterns, https://geodacenter.github.io/
