### Table 17. Simulated Annealing

2006

Cited by 3

### Table 17. Simulated Annealing

### Table 3. Parameters for simulated annealing.

"... In PAGE 14: ...2. Simulated Annealing Parameters SA parameters are presented in Table3 . Final temperature is only 0.... ..."

### Table 2: RelativePerformance of Simulated Annealing and Adaptive Simulated Annealing with

1998

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### Table 2: Results: Simulated Annealing #

"... In PAGE 5: ... As in the homogeneous algorithm, choosing too rapid a decrease for the temperature results in quenching and leads to local minima which are analogous to metastable states of a physical system. Table2 . summarizes the results of 8 di erent annealing schedules for the inhomogeneous algorithm.... In PAGE 5: ... This is to be expected since the probability that three of the four plant sizes are zero is extremely small if Si are randomly assigned values in the range (0,10). From Table2 it is reasonable to infer that the second best solution reported by Klein and Klimpel (1967) is easily found by the annealing algorithm. In our experiments we have also tried a two level annealing approach.... In PAGE 5: ... In our experiments we have also tried a two level annealing approach. For instance, experiments 3 and 5 in Table2 do lead to the best solution reported by Klein and Klimpel (1967) if a local search is carried out in... ..."

### TABLE I PARAMETERS FOR SIMULATED ANNEALING

2003

Cited by 1

### Table 1 Comparison of core/periphery fitness measures using Beck et al. (2003; ND) data

2004

"... In PAGE 5: ....P Boyd, W.J. Fitzgerald, R.J. Beck/Social Networks columns 4 and 5 of Table1 . Column 6 of Table 1 compares the results from the UCINET (Version 6.... In PAGE 5: ... For all 12 groups, all three of these algorithms matched the exhaustive search by consistently finding the global optimum from several starting configurations. [ Table1 about here] From the results in Table 1, the genetic algorithm in UCINET finds the global optimum in two out of our 12 cases. The UCINET fit statistic is among the five best for seven of the 12 cases, and among the ten best for nine of the 12 cases.... In PAGE 5: ... For all 12 groups, all three of these algorithms matched the exhaustive search by consistently finding the global optimum from several starting configurations. [Table 1 about here] From the results in Table1 , the genetic algorithm in UCINET finds the global optimum in two out of our 12 cases. The UCINET fit statistic is among the five best for seven of the 12 cases, and among the ten best for nine of the 12 cases.... In PAGE 7: ... A low probability along with an intuitively high observed fitness value suggests that the observed data may have a core/periphery structure. To illustrate this permutation test, we used Mathematica to program a random permutation generator based upon the observed within group distribution of messages for each of the 12 groups from Table1 . As with the observed data, diagonal cells were also ignored for these permutations.... In PAGE 7: ... For Group 1, for example, no random permutation in each of the 3 runs produced an optimal fitness value equal to or greater than the observed fitness value of 0.867 (see Table1 ). For Group 3, 43 of the random permutations in the first run produced optimal fitness values equal to or greater than the observed fitness value (0.... ..."

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### Table 4: The pseudo-code for Simulated Annealing.

"... In PAGE 11: ... Because random strategies are handled and computed efficiently in LIMIDs, our implementation of Simulated Annealing is obtained by a simple and efficient modification of SPU. Table4 shows the pseudo-code of Simulated Annealing algorithm. A temperature func- tion is used to determine the probability of picking the best move.... ..."

### Table 4: The pseudo-code for Simulated Annealing.

"... In PAGE 12: ... Because random strategies are handled and computed efficiently in LIMIDs, our implementation of Simulated Annealing is obtained by a simple and efficient modification of SPU. Table4 shows the pseudo-code of Simulated Annealing algorithm. A temperature func- tion is used to determine the probability of picking the best move.... ..."