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Review

On the performance analysis of solving the Rubik’s cube using swarm intelligence algorithms

ORCID Icon & ORCID Icon
Article: 2138129 | Received 27 Jun 2022, Accepted 13 Oct 2022, Published online: 30 Oct 2022

Figures & data

Table 1. Observations for particle swarm optimization algorithm.

Figure 1. Iteration vs Fitness graph of PSO.

Figure 1. Iteration vs Fitness graph of PSO.

Table 2. Observations for greedy tree search algorithm.

Figure 2. Iteration vs Fitness graph of greedy tree search.

Figure 2. Iteration vs Fitness graph of greedy tree search.

Table 3. Observations for ant colony optimization algorithm.

Figure 3. Iteration vs Fitness graph of ACO.

Figure 3. Iteration vs Fitness graph of ACO.

Table 4. Observations for discrete krill herd optimization algorithm.

Figure 4. Iteration vs Fitness graph of KHO.

Figure 4. Iteration vs Fitness graph of KHO.

Table 5. Scrambles used for comparative analysis of the algorithms.

Table 6. Observations obtained from the comparative analysis of PSO, greedy tree search, ACO, and DKHO.

Table 7. Mean and standard deviation of the observations obtained from the comparative analysis of the algorithms.

Table 8. Number of times the evaluation function is called by the swarm intelligence algorithms.