### Table 2: Technology Mapping results

"... In PAGE 8: ... The results show that the Boolean approach reduces the number of matching algorithm calls, nd smaller area circuits in better CPU time, and reduces the initial network graph because generic 2-input base function are used. Table2 presents a comparison between SIS and Land for the library 44-2.genlib, which is distributed with the SIS package.... ..."

### Table 6: Constrained Optimization for Minimum $/RPM

"... In PAGE 10: ...45 0.404 Desirability 0 1 Figure 14: Prediction Profiles: Constrained Optimization and Sensitivities The point design optimization results obtained for this example are summarized in Table6 and Table 7. Table 6 contains the optimal setting of the design variables while Table 7 lists the minimal value for the objective function, $/RPM, and the values for the constraints generated by the RSEs as well as the results of a verification run of FLOPS.... In PAGE 10: ...404 Desirability 0 1 Figure 14: Prediction Profiles: Constrained Optimization and Sensitivities The point design optimization results obtained for this example are summarized in Table 6 and Table 7. Table6 contains the optimal setting of the design variables while Table 7 lists the minimal value for the objective function, $/RPM, and the values for the constraints generated by the RSEs as well as the results of a verification run of FLOPS. The right hand column displays the difference of these two values indicating a percentage error for the RSE-based approach.... In PAGE 11: ... The fact that the constraint RSE was formed, however, provides the capability to have a truly noise- constrained vehicle once suppression can be accurately modeled. The optimum aerodynamic design variable settings from Table6 yield a wing planform illustrated in Figure 15. The figure on the right displays the location of the variables and their nominal values.... ..."

### Table 1. Comparison of results for various approaches.

"... In PAGE 8: ... 4. Numerical Results Table1 compares the balance and uniformity (t,s) of (n,2) de Bruijn sequences... In PAGE 9: ... In the case of Algorithm II, the characteristics of the sequences obtained by the optimal mappings with respect to both balance and uniformity criteria are shown. ------------------------- Table1 goes here ------------------------- In Table 1, we observe that: 1. Although Algorithm I generates sequences with optimal uniformity (minimum s), the corresponding balance criterion t is rather large.... In PAGE 9: ... In the case of Algorithm II, the characteristics of the sequences obtained by the optimal mappings with respect to both balance and uniformity criteria are shown. -------------------------Table 1 goes here ------------------------- In Table1 , we observe that: 1. Although Algorithm I generates sequences with optimal uniformity (minimum s), the corresponding balance criterion t is rather large.... ..."

### Table 3. Bound Constrained Problems

1997

"... In PAGE 16: ... There are, in addition, compact representations for the symmetric rank-one (SR1) updating formula, which is particularly appealing in the constrained setting because it is not restricted by the positive de niteness requirement. The recently developed code L-BFGS-B [12], [65] uses a gradient projection ap- proach together with compact limited memory BFGS matrices to solve the bound constrained optimization problem min f(x) subject to l x u: Table3 illustrates the performance of L-BFGS-B on bound constrained problems from the CUTE collection. Once more we use the Newton code of LANCELOT as abenchmark [65].... ..."

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### Table 1. Available collections of digitized hippocampal neurons (pc, pyramidal cells; gc, granule cells: see the text for literature and internet reference). Collection CA3 pc CA1 pc DG gc Interneurons Total

2001

### Table 8.8. Estimated Costs Involved in the Storage of Germplasm in the Active Collection (Field Genebank)

### Table 8.9. Estimated Costs Involved in the Storage of Germplasm in the Base Collection (Seed Genebank)

### Table 1: Results of the Constrained Optimization Problem

"... In PAGE 9: ...961.81381. The first two constraints are active at the optimum. Table1 provides the results obtained using a swarm size of 200 flying for 100 time steps and also with a swarm size of 300 flying for 100 time steps. Five successive trials have been conducted to compute the best, worst and the average values of the objective using the present algorithm.... In PAGE 9: ...he worst, average and the best values are [-6729.7983, -6837.4347, -6883.7124]. It can be clearly observed from Table 2 that our algorithm reports consistent values with much less evaluations when compared with Koziel and Michalewicz (1999). Table1 . Results of the Constrained Optimization Problem Table 2.... ..."

### Table 3b. Solution Statistics for Model 2 (Minimization)

1999

"... In PAGE 4: ...6 Table 2. Problem Statistics Model 1 Model 2 Pt Rows Cols 0/1 Vars Rows Cols 0/1 Vars 1 4398 4568 4568 4398 4568 170 2 4546 4738 4738 4546 4738 192 3 3030 3128 3128 3030 3128 98 4 2774 2921 2921 2774 2921 147 5 5732 5957 5957 5732 5957 225 6 5728 5978 5978 5728 5978 250 7 2538 2658 2658 2538 2658 120 8 3506 3695 3695 3506 3695 189 9 2616 2777 2777 2616 2777 161 10 1680 1758 1758 1680 1758 78 11 5628 5848 5848 5628 5848 220 12 3484 3644 3644 3484 3644 160 13 3700 3833 3833 3700 3833 133 14 4220 4436 4436 4220 4436 216 15 2234 2330 2330 2234 2330 96 16 3823 3949 3949 3823 3949 126 17 4222 4362 4362 4222 4362 140 18 2612 2747 2747 2612 2747 135 19 2400 2484 2484 2400 2484 84 20 2298 2406 2406 2298 2406 108 Table3 a. Solution Statistics for Model 1 (Maximization) Pt Initial First Heuristic Best Best LP Obj.... In PAGE 5: ...) list the elapsed time when the heuristic procedure is first called and the objective value corresponding to the feasible integer solution returned by the heuristic. For Table3 a, the columns Best LP Obj. and Best IP Obj.... In PAGE 5: ... report, respectively, the LP objective bound corresponding to the best node in the remaining branch-and-bound tree and the incumbent objective value corresponding to the best integer feasible solution upon termination of the solution process (10,000 CPU seconds). In Table3 b, the columns Optimal IP Obj., bb nodes, and Elapsed Time report, respectively, the optimal IP objective value, the total number of branch-and-bound tree nodes solved, and the total elapsed time for the solution process.... ..."

### Table 1: Performance Measures for Job-shop Scheduling and Control

2001

"... In PAGE 2: ... Our distributed, evolutionary approach to scheduling avoids these problems by removing the requirement for a truly optimal solution, requiring instead only a towards-optimal (but practical and useful) solution. The goal is to optimize (often) conflicting local and global performance measures (French, 1983), as outlined in columns one and two of Table1 . A secondary goal is to minimize the variance in the global stability measures in column three, in order to maximize the stability of the system.... ..."

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