Fig 1.
Sample solution of a simple vehicle routing problem.
Fig 2.
Distribution of customer locations in problem categories C1, C2, R1, R2, RC1, and RC2.
Fig 3.
Pseudo-code for BCO algorithm.
Fig 4.
Pseudo-code for adaptive BCO algorithm.
Table 1.
Parameter settings for BCO and adaptive BCO algorithms.
Table 2.
Comparison of BCO and adaptive BCO algorithms for VRPTW.
Fig 5.
Comparison of solution performance for distance between BCO and adaptive BCO algorithms.
Fig 6.
Box and Whisker plots for Solomon datasets for adaptive BCO algorithm.
Table 3.
Comparison of results of adaptive BCO-GH and adaptive BCO-SIH algorithms for VRPTW.
Fig 7.
Comparison of distribution of initial population of adaptive BCO-SIH algorithm and that of adaptive BCO-GH algorithm.
Table 4.
Comparison of performance of different approaches against that of adaptive BCO-SIH and adaptive BCO-GH algorithms.
Table 5.
Average rankings of compared algorithms and adaptive BCO-SIH (Friedman’s test).
Table 6.
Holm table for α = 0.05 (Friedman’s test).
Table 7.
Comparison of best-known results in the literature with those of adaptive BCO-SIH.