Hello Andrew, >> Yes. Ampl allows specifying an initial estimation of variables in the >> same way as computable values for parameters, e.g. >> >> var x, >= 0, <= 10, := 3.14159; >> >> Such data are useless for the simplex solver, however, it can be passed >> to the mip solver (to specify some integer feasible solution) or to the >> interior-point solver (to specify a point to start the search from). So >> it is reasonable to implement this feature in Mathprog. >> >> For mip models there might be additional attributes of variables and >> constraints, for example, branching priority, etc.
The "ILOG AMPL CPLEX System, Version 11.0, User’s Guide" http://www.ampl.com/BOOKLETS/amplcplex110userguide.pdf chapter 9, provides an overview which suffixes are supported in AMPL in conjunction with cplex. Variables have the following inbound suffixes .direction is used to specify the branching direction .priority is used to set the branching priority Example: suffix priority IN,integer,>=0,<=9999; # define suffix and value range suffix direction IN,integer,>=-1,<= 1; # define suffix an value range let {i in I, j in J} a[i,j].priority := sum {p in P} d[j,p]; # set suffix let a[0,1].direction := -1; # set suffix Variables have the following outbound suffixes: .up .down .current These indicate the current coefficient in the objective function and the range in which changing the coefficient would leave the current solution optimal. .iis - indicates if a variable constraint renders the problem infeasible and how much the right hand side should be changed to make the problem feasible Constraints have an inbound suffix .lazy - which makes the constraint a lazy constraint handled in a special way by the solver A directive 'lazy' is provided to set how the value of the suffix .lazy is to be used. Constraints have the following outbound suffixes: .up .down .current These indicate the current right hand side of the constraint and the range in which changing the coefficient would leave the current solution optimal. .iis - indicates if the constraint renders the problem infeasible and how much the right hand side should be changed to make the problem infeasible The objective function can have the following suffix: .bestnode - which will cause the solver return the best node instead of the best feasible solution Best regards Xypron -- View this message in context: http://www.nabble.com/FOR-HELP%21-tp20503999p20806370.html Sent from the Gnu - GLPK - Help mailing list archive at Nabble.com. _______________________________________________ Help-glpk mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-glpk
