TY - GEN
T1 - Randomized postoptimization of covering arrays
AU - Nayeri, Peyman
AU - Colbourn, Charles
AU - Konjevod, Goran
N1 - Funding Information:
The second author’s research was supported by DOD grants N00014-08-1-1069 and N00014-08-1-1070 .
PY - 2009
Y1 - 2009
N2 - The construction of covering arrays with the fewest rows remains a challenging problem. Most computational and recursive constructions result in extensive repetition of coverage. While some is necessary, some is not. By reducing the repeated coverage, metaheuristic search techniques typically outperform simpler computational methods, but they have been applied in a limited set of cases. Time constraints often prevent them from finding an array of competitive size. We examine a different approach. Having used a simple computation or construction to find a covering array, we employ a postoptimization technique that repeatedly adjusts the array in order to (sometimes) reduce its number of rows. At every stage the array retains full coverage. We demonstrate its value on a collection of previously best known arrays by eliminating, in some cases, 10% of their rows. In the well-studied case of strength two with twenty factors having ten values each, postoptimization produces a covering array with only 162 rows, improving on a wide variety of computational and combinatorial methods. We identify certain important features of covering arrays for which postoptimization is successful.
AB - The construction of covering arrays with the fewest rows remains a challenging problem. Most computational and recursive constructions result in extensive repetition of coverage. While some is necessary, some is not. By reducing the repeated coverage, metaheuristic search techniques typically outperform simpler computational methods, but they have been applied in a limited set of cases. Time constraints often prevent them from finding an array of competitive size. We examine a different approach. Having used a simple computation or construction to find a covering array, we employ a postoptimization technique that repeatedly adjusts the array in order to (sometimes) reduce its number of rows. At every stage the array retains full coverage. We demonstrate its value on a collection of previously best known arrays by eliminating, in some cases, 10% of their rows. In the well-studied case of strength two with twenty factors having ten values each, postoptimization produces a covering array with only 162 rows, improving on a wide variety of computational and combinatorial methods. We identify certain important features of covering arrays for which postoptimization is successful.
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U2 - 10.1007/978-3-642-10217-2_40
DO - 10.1007/978-3-642-10217-2_40
M3 - Conference contribution
AN - SCOPUS:77951208351
SN - 3642102166
SN - 9783642102165
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 408
EP - 419
BT - Combinatorial Algorithms - 20th International Workshop, IWOCA 2009, Revised Selected Papers
T2 - 20th International Workshop on Combinatorial Algorithms, IWOCA 2009
Y2 - 28 June 2009 through 2 July 2009
ER -