Tabu search for maximal constraint satisfaction problems(14)

Abstract. This paper presents a Tabu Search (TS) algorithm for solving maximal constraint satisfaction problems. The algorithm was tested on a wide range of random instances (up to 500 variables and 30 values). Comparisons were carried out with a min-confl

for MCRW. For the values that both methods could reach at each run (f 11), TS is on average about 3 to 4 times faster than MCRW (in terms of number of moves). For the values between 10 and 4, TS has always a higher number of successful runs than MCRW. Recall that for MCRW, only iterations leading to a real move are counted. Since such iterations leading to a move represent only 25-50% according to the instance (see Table 1), MCRW requires a number of iterations 10 to 15 times higher than that of TS. Data similar to those of Table 2 are available for all the other instances. From the data, we observe very similar behavior.

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