### Table 2: Comparison with ILOG Solver and Ant-P

2001

"... In PAGE 4: ... Let us now compare with a constraint programming system (ILOG solver) and an ant colony optimization method (Ant-P solver), both timings (in seconds) are taken from [23] and divided by a factor 7 corresponding to the SPECint 95 ratio be- tween the processors. Table2 clearly show that adap- tive search is much more performant on this benchmark, which might not be very representative of real-life ap- plications but is a not-to-be-missed CSP favorite.... ..."

Cited by 25

### Table 4: Solving the rehearsal problem using ILOG Solver, with implied constraints on the waiting time for each player

2003

"... In PAGE 11: ...Table 4: Solving the rehearsal problem using ILOG Solver, with implied constraints on the waiting time for each player Table4 shows the effect of adding this implied constraint on solving the rehearsal prob- lem (with the symmetry constraint a107 a26a172a90 a107 a82 ). With both search orders, it reduces search dramatically.... ..."

Cited by 2

### Table IV. Filtering performance for the Gough-Stewart problem Interval Newton Ilog Solver Quad RealPaver

### Table IV. Randomized rapid restarts (RRR) versus determinis- tic versions of backtrack search procedures (Satz solver used on SAT encodings; Ilog solver on CSP encodings).

2000

Cited by 91

### Table IV. Randomized rapid restarts (RRR) versus determin- istic versions of backtrack search procedures (Satz solver used on SAT encodings; Ilog solver on CSP encodings).

2000

Cited by 91

### Table 1.8. Randomized rapid restarts (RRR) versus deterministic versions of backtrack search procedures (Satz solver used on SAT encodings; Ilog solver on CSP encodings).

### Table 6. Results: Golomb ruler. Hardware: 2GHz Athlon XP, 256Mb RAM. Software: Java 1.4.1, Ilog Solver 5.2.

2002

"... In PAGE 10: ... The transformed mod- els are similar to that presented in Table 5. Results are given in Table6... In PAGE 11: ... Given the final model of the 3-tick ruler, it is not difficult for a human to see how this model could be generalised to a formula- tion for the entire problem class. The comparative results of the basic and final models presented in Table6 indicate that the effort expended on such a process could easily be justified as a14 grows larger. A machine learning tool such as HR [3] or Progol [12] might be used to aid in the generalisation process.... ..."

Cited by 17