# Changeset 784 for stable/0.4

Ignore:
Timestamp:
Oct 30, 2011 3:00:54 PM (8 years ago)
Message:

fixes to parameter docu

File:
1 edited

### Legend:

Unmodified
 r692 "to find feasible solutions for the problem. " "The heuristic may take some time, but usually finds good solutions. " "Recommended if you want good upper bounds and have Cplex." "Recommended if you want good upper bounds and have Cplex. " "Not recommended if you do not have Cplex"); "Specify the maximum time allowed for the Iterative Rounding heuristic", -1, "Maximum CPU time employed by the Iterative Rounding heuristic; " "if no solution found in this time, failure is reported." "if no solution found in this time, failure is reported. " "This overrides the CPU time set by Aggressiveness if positive."); 0, 2, 1, "Set the aggressiveness of the heuristic; i.e., how many iterations " "should be run, and with which parameters. The maximum time can be" "overridden by setting the _time and _time_firstcall options." "should be run, and with which parameters. The maximum time can be " "overridden by setting the _time and _time_firstcall options. " "0 = non aggressive, 1 = standard (default), 2 = aggressive."); "Max number of points rounded at the beginning of Iterative Rounding", 1, 5, "Number of different points (obtained solving a log-barrier problem)" "that the heuristic will try to round at most, during its execution" "Number of different points (obtained solving a log-barrier problem) " "that the heuristic will try to round at most, during its execution " "at the root node (i.e. the F-IR heuristic). Default 5."); "Omega parameter of the Iterative Rounding heuristic", 0, true, 1, true, 0.2, "Set the omega parameter of the heuristic, which represents a" "multiplicative factor for the minimum log-barrier parameter" "of the NLP which is solved to obtain feasible points. This" "corresponds to \\omega' in the paper. Default 0.2."); "Set the omega parameter of the heuristic, which represents a " "multiplicative factor for the minimum log-barrier parameter " "of the NLP which is solved to obtain feasible points. This " "corresponds to $\\omega'$ in the paper. Default 0.2."); roptions -> AddLowerBoundedIntegerOption "Base rhs of the local branching constraint for Iterative Rounding", 0, 15, "Base rhs for the local branching constraint that defines a" "neighbourhood of the local incumbent. The base rhs is modified by" "the algorithm according to variable bounds. This corresponds to" "Base rhs for the local branching constraint that defines a " "neighbourhood of the local incumbent. The base rhs is modified by " "the algorithm according to variable bounds. This corresponds to " "k' in the paper. Default 15.");