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Minimizing the total trim loss is the objective function (1) of the model.
The objective function considered in this paper minimizes the total trim loss.
It is obvious that SA outperforms TS to get a better minimum number of stocks used or less total trim loss (i.e., total trim loss ratio) so that the mean of the total trim loss ratio of SA for the problems is 6.49percentt while it is 7.45percentt in TS. Figure 3 shows CPU times of two algorithms for the twenty mentioned problems.
The total trim loss ratio can be defined by: Total trim loss ratio = Sum of trim loss of all used stocks Stocks used × standard length × 100 % Open image in new window (5).
To compare the efficiency of these algorithms with each other, the six large-scale problems (15, 16, 17, 18, 19 and 20) are solved and the total stocks used in each solution, the total trim losses and total trim loss ratio of each algorithm are represented in Table 3.
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3 shallots, roughly chopped. 2 medium bunches broccoli rabe (about 1 1/2 pounds total), trimmed and cut into 2-inch and 3-inch pieces.
The total TRIM-Diabetes was significantly correlated (r = 0.63) with the Global Satisfaction scale of the TSQM.
The total TRIM-Weight was able to distinguish between groups likely or not likely to recommend their current treatment to a friend (F = 26.69, p < 0.001).
The total TRIM-Diabetes was able to distinguish between willingness of respondents to change their diabetes treatment (F = 83.7, p < 0.001).
The total TRIM-Weight was not able to discriminate the length of time willing to stay on the current treatment, as this was likely confounded by how long the patients had already been on their treatment.
The Total TRIM-Weight significantly correlated (r = 0.62) with the overall life satisfaction scale of the Q-LES-Q and the Psychological Health subscale (TRIM-Weight) had a significant association with the SF-12 mental component summary (r = 0.60).
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