### Table 1: Number of Function Evaluations of selected problems using DE, DE-QN, SA and TS

"... In PAGE 11: ... By trial and error, incorporating QN into DE at 500 iterations was found to be the most computationally efficient. As seen from Table1 , the number of function evaluations required for solving the benchmark problems by DE-QN is considerably reduced compared to just using DE alone, indicating the local optimizer (QN) is able to locate the global minimum efficiently when DE has done the hard work at the beginning. Thus, DE is successfully combined with QN to reduce the computational time while maintaining the reliability.... ..."

### Table 3: Absolute improvement with tabu search using di erent parameters

"... In PAGE 15: ... Using this good initial solution we applied tabu search with di erent values for kmax to our test set. The corresponding results are presented in Table3 . The table contains the following information: Neigh: Denotes the used neighborhood.... ..."

### Table 2. Comparison of tabu search with different tabusize

"... In PAGE 11: ... The stopping rule Nmax represents the number of consecutive iterations allowed for the search to continue without cost improvement. The experimental results are illustrated in Table2 and 3. The RCBA algorithm was employed as an initial heuristic for all experiments.... In PAGE 11: ... In particular, a fixed or variable tabusize including its scale should be determined through various experimental simulations. In Table2 , fixed tabusize n/4, n/2 and a uniformly distributed tabusize ranged from n/4 to n/2 are compared with the initial solution for each problem. From the table, we conclude that tabusize n/4 is appropriate for the problem structure considered in this paper.... In PAGE 11: ... Based on the experiments by various Nmax, we see that the stopping criteria Nmax with 2n is appropriate for all the problems. Table2 . Comparison of tabu search with different tabusize Table 3.... ..."

### Table 3: Performance of Tabu Search and Genetic Algorithms

"... In PAGE 9: ...ilk test for normality at an alpha level of 0.1. The results of the tabu search were compared to the genetic algorithm operating on the new facil- ity locations as described in [11]. The results of these experiments are given in Table3 .The last column of Table 3 indicates the alpha level of significance of not rejecting the hypothesis that the means of the solutions found by both the GA and tabu search are equal.... In PAGE 9: ... The results of these experiments are given in Table 3.The last column of Table3 indicates the alpha level of significance of not rejecting the hypothesis that the means of the solutions found by both the GA and tabu search are equal. The solutions found by both the GA and tabu search were tested for normality using the Shapiro-Wilk test.... In PAGE 9: ...1 are indicated in the table. As Table3 shows, the GA finds significantly better solutions for the larger problems, i.e.... In PAGE 16: ... As indicated in Table 5, the average number of iterations for tabu search to map these basins quickly grows very large. This is consistent with the results presented in Table3 . Tabu search is unable to escape from the large local minima, while the GA, with its strong random search component is able to easily jump between local minima.... ..."

### Table 3: Performance of Tabu Search and Genetic Algorithms

"... In PAGE 9: ...ilk test for normality at an alpha level of 0.1. The results of the tabu search were compared to the genetic algorithm operating on the new facil- ity locations as described in [11]. The results of these experiments are given in Table3 .The last column of Table 3 indicates the alpha level of significance of not rejecting the hypothesis that the means of the solutions found by both the GA and tabu search are equal.... In PAGE 9: ... The results of these experiments are given in Table 3.The last column of Table3 indicates the alpha level of significance of not rejecting the hypothesis that the means of the solutions found by both the GA and tabu search are equal. The solutions found by both the GA and tabu search were tested for normality using the Shapiro-Wilk test.... In PAGE 9: ...1 are indicated in the table. As Table3 shows, the GA finds significantly better solutions for the larger problems, i.e.... In PAGE 16: ... As indicated in Table 5, the average number of iterations for tabu search to map these basins quickly grows very large. This is consistent with the results presented in Table3 . Tabu search is unable to escape from the large local minima, while the GA, with its strong random search component is able to easily jump between local minima.... ..."

### Table 3: Results for the CELAR problems using Tabu Search

"... In PAGE 15: ... Although the double-update approach constitutes an improvement on the regular Hop eld and Boltzmann Machine models, the latter techniques cannot be used for comparison, since, as already discussed, they are not capable of tackling hard problems of the type considered here. Table3 shows the results reported in [32], where Tabu Search is applied to the same problems. In this case 20 experiments were carried out for each problem instance on a 130MHz DEC Alpha machine.... In PAGE 15: ... In this case 20 experiments were carried out for each problem instance on a 130MHz DEC Alpha machine. We should note here that Table3 refers to results obtained without any kind of pre-processing. gt;From the comparison of Tables 2 and 3 we can see that solutions are obtained in about the same time using both methods (as the experiments were not carried out on the... ..."

### Table 2: tabu search heuristic

2005

"... In PAGE 16: ... 6.2 Results Table2 shows the results of both the initial and nal solutions of tabu search. The percentage deviation from the best (i.... In PAGE 16: ... This number provides us with the number of local minima encountered. As with Table2 , Table 3 also shows that results improve with an increasing value of t, but this is not the case for instances pr3a-pr3c. Solutions to instances pr3b and pr3c have the same number... ..."

### Table 4: Summary of Results of Numeric Simulations on 13x13x13 Table Using Tabu Search

"... In PAGE 9: ...00 1.00 Table4 : Summary of Results of Numeric Simulations on 13x13x13 Table Using Linear Programming * = compromise solution 4. CONTROLLED TABULAR ADJUSTMENT USING TABU SEARCH 25.... ..."

### Table 3: Comparison of Algorithms in Terms of Speed and Efficiency

2002

"... In PAGE 10: ... This modification will affect the speed but not the efficiency for constructing OAs. Table3 shows the comparisons of the algorithms in terms... In PAGE 11: ... In the simulation, we repeat the Fedorov algorithm 1,000 times for OA(12, 211) and OA(16, 215) because it is very slow, and repeat other algorithms 10,000 times for all arrays. Table3 shows clearly that our algorithm performs the best and the Fedorov algorithm performs least well in both speed and efficiency. The Fedorov algorithm is slow because it uses an exhaustive search of points for improvement and because it uses D-optimality as the objective function which involves real-valued matrix operations.... ..."

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### Table 1: Improving loop efficiency. Loop to Improve Improved Loop

"... In PAGE 4: ...Consider improving the simple loop shown on the left in Table1 . The purpose of this experiment is to design a more efficient addressing mode which miti- gates loop overhead.... In PAGE 4: ... To test the IND X+ addressing mode, a loop was created to clear a block of memory. In the original method (left side of Table1 ), the CLR operation uses the IND X addressing mode. This loop requires 13 machines cycles to execute.... ..."