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Minimal solution, i.e. the smallest solution found by any software included in the study for a specific tree pair.
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The maximum gap between the best bound found by CPLEX within 10 hours and the best solution found by our VNS is as small as 3.4%.
The maximum gap between the best and average solution found by VNS is as small as 0.03% (0.6%) for the smaller (larger) instances.
On average, the solutions found are slightly further from the known solution than the starting points are (Table 1, row 3), and have 97% smaller error.
The solutions found by GP typically use a rather small number of features (i.e. terminals).
Hence, this is a relative measure of how far are the solutions: a smaller value means that solutions found are close between the methods tested.
The results obtained are compared with some known theoretical solutions, found by the small parameter method, and with experimental data corresponding to the steady state regime.
This might improve the descriptive characteristics of the smaller groups found in the 7-cluster solution of this study.
Our computational experiments show that the proposed heuristic returns very high-quality solutions for this difficult problem, matches all optimal solutions found for small and medium-scale benchmark instances, and improves upon existing algorithms for two important special cases: the vehicle routing problem with private fleet and common carrier, and the capacitated profitable tour problem.
For smaller α, a small-slope late-time solution is found that agrees with the numerical solution for α=30°.
By testing small overlapping solutions, we found that the negative edge effects extend a few degrees at most, so our 10° cutoff is probably conservative.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com