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Research Article

Analysis of dependence of grey wolf optimizer to shift-transformations and its shift-invariant improved methods adaptively controlling the search areas

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Pages 66-79 | Received 25 Sep 2023, Accepted 22 Jan 2024, Published online: 28 Feb 2024

Figures & data

Figure 1. Relations of d(p,i), x(p) and x(i).

Figure 1. Relations of d(p,i), x(p) and x(i).

Table 1. Benchmark problems.

Figure 2. Means of Δx(α,i)(t), d(α,i)(t), and f(x(α)(t)) for four shift vectors.

Figure 2. Means of ‖Δx(α,i)(t)‖, ‖d(α,i)(t)‖, and f(x(α)(t)) for four shift vectors.

Table 2. Comparison of results obtained by GWO for 20 benchmark problems (P1) and (P2) with three kinds of shift vectors (ρ=0.1,0.5,0.9).

Figure 3. Relation between dˆ(p,i)(t) and v(p)(t) when cm=3 and u(p,i)=1.5.

Figure 3. Relation between dˆ(p,i)(t) and v(p)(t) when cm=3 and u(p,i)=1.5.

Table 3. Comparison of results obtained by GWO-SRs with seven different reference points and GWO-R with μ(1,2) for 20 benchmark problems (P1).

Table 4. Comparison of PSO, FA, GWO-SR and GWO-AS for 50-dimensional problems (fmax=1200000).

Table 5. Comparison of PSO, FA, GWO-SR and GWO-AS for 200-dimensional problems ( fmax=4800000 ).

Figure 4. Means of the best function values obtained by four methods, PSO, FA, GWO-SR and GWO-AS, until function evaluation count per agent for 50-dimensional six benchmark problems.

Figure 4. Means of the best function values obtained by four methods, PSO, FA, GWO-SR and GWO-AS, until function evaluation count per agent for 50-dimensional six benchmark problems.

Figure 5. Means of |W(k)(t+1)|, k{1,2,3} for three candidates on 50 trials at each count when GWO-AS is applied to 50-dimensional four benchmark problems.

Figure 5. Means of |W(k)(t+1)|, k∈{1,2,3} for three candidates on 50 trials at each count when GWO-AS is applied to 50-dimensional four benchmark problems.