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Table 3 Conclusion of literature review

From: Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matches

Algorithms

Run time

Input

Limitations

Gale–Shapley (Gale and Shapley 1962; Roth 1984)

\(n \times m\)

\(n \times m\) matrix for each set of vertices (List of preferences)

Hopcroft-Karp (Micali and Vazirani 1980; Motwani 1994)

\((n \times m - \min (n,m))\sqrt {n + m}\)

\(n \times m\) matrix (A unweighted bipartite graph)

Does not satisfy assumption 2 and 1

Ford-Fulkerson (Backman and Huynh 2018)

\((n \times m - \min (n,m)) \times f\)

\(n \times m\) matrix (A unweighted bipartite graph) and capacity of each vertices

Does not satisfy assumption 2

Hungarian (Kuhn 1956)

\(\begin{gathered} (n + m)^{3} = n^{3} + m^{3} + \hfill \\ 2n^{2} m + 2nm^{2} + 1 \hfill \\ \end{gathered}\)

\(n \times m\) matrix (Cost of matching vertices)

Does not satisfy assumption 1

Cycle cancelling (Shepherd and Zhang 1999; Nassir et al. 2014)

\((n \times m - \min (n,m)) \times C \times U\)

\(n \times m\) matrix (Cost of matching vertices) and capacity and supply/demand of vertices

LP Network Simplex (Orlin 1997; Tarjan 1997)

\(\begin{gathered} (n + m)(n \times m - \min (n,m)) \hfill \\ \log (n + m)\log ((n + m)C) \hfill \\ \end{gathered}\)

\(n \times m\) matrix (Cost of matching vertices)

Does not satisfy assumption 1