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W. Sun, J. Hao, X. Lai, Q. Wu, and ;. .. , 25 2.2 The classes matching procedure by a complete bipartite graph H, Proceedings of the Genetic and Evolutionary Computation Conference, pp.369-376, 2017.
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G. .. , , p.30

, Influence of the increment/decrement value of the penalty efficient, p.66

, Flow chart of the iterated backtrack-based removal algorithm for finding k-VCS in a graph

. .. Update-procedure, 33 2.2 Comparative results of RMA with state-of-the-art algorithms MACOL and PLSCOL on 19 easy benchmark instances, p.35

, Comparative results of RMA with state-of-the-art algorithms MACOL and PLSCOL on 20 difficult benchmark instances. The best results are in bold, p.36

, Assessment of different number of the parents. The better results are in bold, p.37

. .. , Assessment of different strategies. The better results are in bold, p.38

, Analysis of the influence of the perturbation on the performance of the RMA algorithm. The better results are in bold

, Comparative results of FISA with state-of-the-art algorithms on the 73 benchmark instances

, Comparative results of the FISA algorithm with 3 different values of ? on the 26 instances. The best results are in bold

, Analysis of the influence of the perturbation on the performance of the FISA algorithm

, Settings of important parameters, p.61

, Comparative results of AFISA with state-of-the-art algorithms on the 46 DIMACS benchmark instances. Improved upper bounds are indicated in bold, p.62

, Comparative results of AFISA with state-of-the-art algorithms on the 35 pxx benchmark instances. Improved upper bounds are indicated in bold, p.63

, Comparative results of AFISA with state-of-the-art algorithms on the 30 rxx benchmark instances. Improved upper bounds are indicated in bold, p.64

, Comparative results of FISA with CPLEX on the additional set of 50 larger DI-MACS/COLOR instances. Improved upper bounds are indicated in bold, p.64

, Assessment of searching both feasible and infeasible solutions

, Assessment of the perturbation strategy. The better results are in bold, p.68

, Comparative results of IBR with state-of-the-art algorithm on the first category of instances

, Comparative results of IBR with state-of-the-art algorithm on the second category of instances

, Comparative results of IBR with state-of-the-art algorithm on the third category of instances. Improved results are indicated in bold

, Comparative results of IBR with state-of-the-art algorithm on the fourth category of instances. Improved results are indicated in bold

, Comparative results of the IBR algorithm with two different backtrack strategies. Improved results are indicated in bold

, Analysis of the influence of the perturbation on the performance of the IBR algorithm. The BR algorithm is obtained by replacing the perturbation procedure of the IBR algorithm with a restart strategy. Improved results are indicated in bold, p.86

, IR is obtained by disabling the backtracking procedure, vol.87

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