### Table 1: Parallelepiped constraints on the problem variables variables constraints

"... In PAGE 4: ... The total number of constraints is 51. The parallelepiped constraints on the problem variables are summarized in Table1 . To prevent the generation of large contact forces, we also impose the additional constraints on the joint torques, limiting their absolute values by 0.... ..."

### Table 1: Computational complexity of constraint planning problems. Cycles in the constraint

"... In PAGE 5: ... Indeed, a general computational result states that a restriction imposed on a solution does not necessarily make the corresponding problem easier [Papadimitriou 94]. Table1 shows the computational complexity of some existing constraint planning problems. 4 An NP-complete planning problem with method restriction De nition 3 The method restriction imposes that every constraint method of a given problem must use all of the variables in the constraint either as an input or an output variable.... ..."

### Table 1: Example Problem Constraints

1996

"... In PAGE 6: ... The space of all possible designs in the ACDS representation is given by the set of all catalog-agent domains: i U [cai]. Table1 shows the five constraints4: motor_select, cable_select, cable_length, dollar and fail_rate found in the example. The fail_rate and dollar constraints are static (their... ..."

Cited by 18

### Table 4: Results for Sequentially Related Constraint Problems with CFSQP

1997

"... In PAGE 63: ... It can be checked that the second order su cient conditions of optimality are not satis ed at the known optimal solution for problems 26, 27, 46 and 47. Table4 contains the results for problems with a set (or sets) of sequentially related contraints solved via the algorithm FSQP-SR. All problems in this table are discretized semi-in nite programs.... In PAGE 64: ... Once again, the norm requirement for the SQP direction, eps, was set to 10?4 for all problems. All problems except for sch u3, which is taken from [14], are the same as the corresponding problems in Table4 , except that they are rewritten in minimax form. In other words, in the original reference they were posed in the form: min x2IRn+1 xn+1 s.... ..."

Cited by 33

### Table 2: Objective functions, constraints and optimization problems

2003

Cited by 4

### Table 3. A summary of constraints required Problem

### Table 2 The average number of constraints per problem

1994

### Table 1: Constraints to optimization problems by difierent sets J J Constraints

### Table 2: Serial and parallel run times of the multi-constraint graph partitioner for a three-constraint problem on

1998

"... In PAGE 18: ... Run Time Results. Table2 compares the run times of the parallel multi-constraint graph partitioning algorithm with the serial multi-constraint algorithm implemented in the MeTiS library [5] for mrng1. These results show only modest speedups for the parallel partitioner.... ..."

Cited by 117

### Table 1 (expressing constraints in models for scheduling problems)

"... In PAGE 17: ...Table1... ..."