By Ageev A.A.

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**Extra resources for A 3/2-approximation algorithm for the jump number of interval orders**

**Sample text**

N). Each bit mask is of length N, and contains K + I ones. The ls in a bit mask indicate the bits in an individual that are used to determine the value of the ith subfunction. Given these parameters, one can construct a random NK landscapes as follows: A. Construct an N by 2 K+I table, X. B. Fill X with random numbers, typically from a standard uniform distribution. Given the table X, and the bit masks, one determines the fitness of an individual as follows: C. For each bit mask bi, select out the substring of the individual that correspond with the K + I one-valued bits in that bit mask.

W 9 NK-landscapes are uncorrelated when K = N - 1, but our evidence shows that the structure in NK-landscapes deteriorates rapidly as K increases, becoming such that none of the studied algorithms can effectively exploit it when K > 12 for N up to 200. This K-region is remarkably similar for a wide range of N's. 9 Finally, the advantage that random bit-climbers enjoy over CHC-HUX depends on three things: the number of random restarts executed (a function of the total number of trials allotted and the depth of attraction basins in the landscape), the number of attraction basins in the space, and the size of the attraction basin containing the global optimum relative to the other basins in the space.

4 Walsh-based Landscapes Consider a search space defined over length L binary strings. In terms of the Walsh coefficients, define the fitness of an individual as 2L L j=0 i=1 where x is the bit string representing the individual, xi is the ith bit in that string, wj is the Walsh coefficient corresponding to the partition (bit mask) numbered j, J is the bit mask (which is the N-bit binary integer representation of j), Ji is the ith bit in the bit mask, and ~ is the function described in Table 1.

### A 3/2-approximation algorithm for the jump number of interval orders by Ageev A.A.

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