Strip nesting problems are well known to be of NP-hard complexity, even in simple cases. A multitude of algorithms now exist that aim at solving such problems efficiently. The experimentation system described here helps users with industrial applications to decide which algorithm suits their requirements best. As an illustration, it is applied to three algorithms, based on: simulated annealing (SA), tabu search (TS), and ant colony optimization (ACO). The system can be treated as an input-output system, in which the parameters of the problem and the algorithms for solving the problem are the inputs, and the introduced measures of algorithms' quality are the outputs. Experiments are conducted in accordance with a two-stage approach. At the first stage, the tuning process for each algorithm is made. At the second stage, the efficiencies of the optimized algorithms are compared. In the paper, the results of the comparison obtained with the benchmark databases are discussed, and conclusions concerning efficiency of the considered algorithms are drawn accordingly.
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