Heuristics and meta-heuristics for 2-layer straight line crossing minimization Original Research Article

This paper presents extensive computational experiments to compare 12 heuristics and 2 meta-heuristics for the problem of minimizing straight-line crossings in a 2-layer graph. These experiments show that the performance of the heuristics (largely based on simple ordering rules) drastically deteriorates as the graphs become sparser. A tabu search metaheuristic yields the best results for relatively dense graphs, with a GRASP implementation as close second. Furthermore, the GRASP approach outperforms all other approaches when tackling low-density graphs.