Class ABA_MASTER is the central object of the framework. The most important tasks of the class ABA_MASTER is the management of the implicit enumeration. Moreover, it provides already default implementations for constraints, cutting planes, and variables pools.
#include <master.h>
Inheritance diagram for ABA_MASTER::
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Optimal, Error, OutOfMemory, Unprocessed,
Silent, Statistics, Subproblem, LinearProgram,
Full }
This enumeration defines the two currently implemented branching variable selection strategies.
This enumeration provides various methods for the initialization of the primal bound.
This enumeration defines the ways for automatic constraint elimination during the cutting plane phase.
This enumeration defines the ways for automatic variable elimination during the column generation algorithm.
This enumeration defines what kind of output can be generated for the VBCTOOL.
SoPlex, SYMPHONY, Vol, XPRESS_MP }
This enumeration defines which solvers can be used to solve theLP-relaxations.
The destructor.
This version of the function enumerationStrategy() changes the enumeration strategy.
Analyzes the enumeration strategy set in the parameter file { .abacus} and calls the corresponding comparison function for the subproblems s1 and s2. This function should be redefined for application specific enumeration strategies.
Can be used to check if the guarantee requirements are fulfilled, i.e., the difference between upper bound and the lower bound in respect to the lowerBound is less than this guarantee value in percent.
Can be used to control the correctness of the optimization if the value of the optimum solution has been loaded.
Opens the file specified with the parameter { OptimumFileName} in the configuration file { .abacus} and tries to find a line with the name of the problem instance (as specified in the constructor of ABA_MASTER) as first string.
Writes all parameters of the class ABA_MASTER together with their values to the global output stream.
This version of the function nbranchingVariableCandidates() sets the number of tested branching variable candidates.
This version of the function requiredGuarantee() changes the guarantee specification.
This version of the function maxLevel() changes the maximal enumeration depth.
The function maxCowTime().
This version of the function maxCowTime() set the maximal wall-clock time for the optimization.
This version of function objInteger() sets the assumption that the objective function values of all feasible solutions are integer.
The function tailOffNLp().
The function tailOffPercent().
This version of the function tailOffPercent() sets the minimal change of the dual bound for the tailing off analysis.
The version of the function outLevel() sets the output mode.
This version of the function logLevel() sets the output mode for the log-file.
Sets the number of optimizations of a subproblem until sons are created in ABA_SUB::branching().
This version of the function pricingFreq() sets the number of linear programs being solved between two additional pricing steps.
This version of the function skipFactor() sets the frequency for constraint and variable generation.
This version of the function skippingMode() sets the skipping strategy.
Sets the maximal number of constraints that are added in an iteration of the cutting plane algorithm.
Changes the maximal number of constraints that are buffered in an iteration of the cutting plane algorithm.
Changes the maximal number of variables that are added in an iteration of the subproblem optimization.
Changes the maximal number of variables that are buffered in an iteration of the subproblem optimization.
Changes the default value for the maximal number of iterations of the optimization of a subproblem.
This version of the function eliminateFixedSet() can be used to turn the elimination of fixed and set variables on or off.
Turns the output of the average distance of the added cuts from the fractional solution on or off.
bounds
In order to embed both minimization and maximization problems in this system we work internally with primal bounds, i.e., a value which is worse than the best known solution (often a value of a feasible solution), and dual bounds, i.e., a bound which is better than the best known solution. Primal and dual bounds are then interpreted as lower or upper bounds according to the sense of the optimization.
This version of the function primalBound() sets the primal bound to x and makes a new entry in the solution history. It is an error if the primal bound gets worse.
This version of the function dualBound() sets the dual bound to x and makes a new entry in the solution history.
We use this function ,e.g., to adapt the enumeration strategy in the DiveAndBest-Strategy.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { STATUS[0]=="Optimal"}).
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { OUTLEVEL[0]=="Silent"}).
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { ENUMSTRAT[0]=="BestFirst"}).
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { BRANCHINGSTRAT[0]=="CloseHalf"}).
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { PRIMALBOUNDMODE[0]=="None"}).
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { SKIPPINGMODE[0]=="None"}).
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { CONELIMMODE[0]=="None"}).
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { VARELIMMODE[0]=="None"}).
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { VBCMODE[0]=="None"}).
Array for the literal values for possible Osi solvers.
Is overloaded such that also a first set of cutting planes can be inserted into the cutting plane pool.
Can be used to initialize the sense of the optimization in derived classes, if this has not been already performed when the constructor of ABA_MASTER has been called.
Is called from the function bestFirstSearch() and from the function depthFirstSearch() if the subproblems s1 and s2 have the same priority.
Implements the depth first search enumeration strategy, i.e., the subproblem with maximum level is selected.
Implements the breadth first search enumeration strategy, i.e., the subproblem with minimum level is selected.
Performs depth-first search until a feasible solution is found, then the search process is continued with best-first search.
Is only a dummy. This function can be used to initialize parameters of derived classes and to overwrite parameters read from the file { .abacus} by the function ().
The default implementation of initializeOptimization() does nothing.
The default implementation of terminateOptimization() does nothing.
Reads the parameter-file { .abacus}, which is searched in the directory given by the environment variable ABACUS_DIR, and calls the virtual function initializeParameters() which can initialize parameters of derived classes and overwrite parameters of this class.
Initializes the LP solver specific default Parameters if they are not read from the parameter-file { .abacus}.
Adds the subproblem sub to the stream storing information for graphical output of the enumeration tree if this logging is turned on.
Updates the node information in the node with number id by writing the lower bound lb and the upper bound ub to the node.
Increments the counter for linear programs and should be called in each optimization call of the LP-relaxation.
Increments the counter of the number of fixed variables by n.
Increments the counter for the total number of added constraints by n.
Increments the counter for the total number of removed constraints by n.
Increments the counter for the total number of added variables by n.
Increments the counter for the total number of removed variables by n.
The number of candidates that are evaluated for branching on variables.
The number of subproblems already selected from the list of open subproblems.
Ouput for the Tree Interface is generated depending on the value of this variable.
The guarantee in percent which should be reached when the optimization stops.
true, if all objective function values of feasible solutions are assumed to be integer.
The minimal number of rounds, i.e., number of subproblem optimizations, a subproblem is dormant, i.e., it is not selected from the set of open subproblem if its status is Dormant, if possible.
The frequency constraints or variables are generated depending on the skipping mode.
Either constraints are generated only every skipFactor_ subproblem (SkipByNode) only every skipFactor_ level (SkipByLevel).
The maximal number of added constraints per iteration of the cutting plane algorithm.
The maximal number of added variables per iteration of the column generation algorithm.
The maximal number of iterations of the cutting plane/column generation algorithm in the subproblem.
If true, then an already earlier processed node is reoptimized if it becomes the new root of the remaining \ tree.
The name of a file storing a list of optimum solutions of problem instances.
If true then the average distance of the added cutting planes is output every iteration of the cutting plane algorithm.
The way constraints are automatically eliminated in the cutting plane algorithm.
The way variables are automatically eliminated in the column generation algorithm.
The tolerance for the elimination of constraints by the mode NonBinding/.
The tolerance for the elimination of variables by the mode ReducedCost.
The number of iterations an elimination criterion must be satisfied until a constraint can be removed.
The number of iterations an elimination criterion must be satisfied until a variable can be removed.
The timer for the cpu time spent in the heuristics for the computation of feasible solutions.
Class ABA_MASTER is the central object of the framework. The most important tasks of the class ABA_MASTER is the management of the implicit enumeration. Moreover, it provides already default implementations for constraints, cutting planes, and variables pools.
Definition at line 76 of file master.h.
The various statuses of the optimization process.
Definition at line 109 of file master.h.
This enumeration defines the different output levels:
Definition at line 131 of file master.h.
Definition at line 158 of file master.h.
This enumeration defines the two currently implemented branching variable selection strategies.
Definition at line 175 of file master.h.
This enumeration provides various methods for the initialization of the primal bound.
The modes OptimalPrimalBound and OptimalOnePrimalBound can be useful in the testing phase. For these modes the value of an optimum solution must stored in the file given by the parameter { OptimumFileName} in the parameter file.
Definition at line 202 of file master.h.
The way nodes are skipped for the generation of cuts.
Definition at line 218 of file master.h.
This enumeration defines the ways for automatic constraint elimination during the cutting plane phase.
Definition at line 233 of file master.h.
This enumeration defines the ways for automatic variable elimination during the column generation algorithm.
Definition at line 249 of file master.h.
This enumeration defines what kind of output can be generated for the VBCTOOL.
Definition at line 266 of file master.h.
This enumeration defines which solvers can be used to solve theLP-relaxations.
Definition at line 280 of file master.h.
The constructor.
The members primalBound_ and dualBound_ stay uninitialized since this can only be done when the sense of optimization (minimization or maximization) is known. The initialization is performed automatically in the function optimize().
The destructor.
Performs the optimization by .
The status of the optimization.
The value of the global lower bound.
Definition at line 1885 of file master.h.
The value of the global upper bound.
Definition at line 1891 of file master.h.
The value of the primal bound, i.e., the lowerBound() for a maximization problem and the upperBound() for a minimization problem, respectively.
Definition at line 1897 of file master.h.
This version of the function primalBound() sets the primal bound to x and makes a new entry in the solution history. It is an error if the primal bound gets worse.
The value of the dual bound, i.e., the upperBound() for a maximization problem and the lowerBound() for a minimization problem, respectively.
Definition at line 1902 of file master.h.
This version of the function dualBound() sets the dual bound to x and makes a new entry in the solution history.
It is an error if the dual bound gets worse.
true If x is better than the best known dual bound.
false otherwise.
Can be used to compare a value with the one of the best known primal bound.
If the objective function values of all feasible solutions are integer, then we do not have to be so carefully.
true If x is not better than the best known primal bound,
false otherwise.
Can be used to check if a value is better than the best know primal bound.
true If x is better than the best known primal bound,
false otherwise.
We use this function ,e.g., to adapt the enumeration strategy in the DiveAndBest-Strategy.
This function is only correct if any primal bound better than plus/minus infinity corresponds to a feasible solution.
true If a feasible solution of the optimization problem has been found.
false otherwise.
The enumeration strategy.
Definition at line 2251 of file master.h.
This version of the function enumerationStrategy() changes the enumeration strategy.
Definition at line 2256 of file master.h.
Analyzes the enumeration strategy set in the parameter file { .abacus} and calls the corresponding comparison function for the subproblems s1 and s2. This function should be redefined for application specific enumeration strategies.
1 If s1 has higher priority than s2
0 if s2 has higher priority it returns -1, and if both subproblems have equal priority
Can be used to check if the guarantee requirements are fulfilled, i.e., the difference between upper bound and the lower bound in respect to the lowerBound is less than this guarantee value in percent.
If the lower bound is zero, but the upper bound is nonzero, we cannot give any guarantee.
A guarantee for a solution can only be given if the pricing problem is solved exactly or no column generation is performed at all.
true If the guarantee requirements are fulfilled,
false otherwise.
Can be used to access the guarantee which can be given for the best known feasible solution.
It is an error to call this function if the lower bound is zero, but the upper bound is nonzero.
The guarantee for best known feasible solution in percent.
Writes the guarantee nicely formated on the output stream associated with this object.
If no bounds are available, or the lower bound is zero, but the upper bound is nonzero, then we cannot give any guarantee.
Can be used to control the correctness of the optimization if the value of the optimum solution has been loaded.
This is done, if a file storing the optimum value is specified with the parameter { OptimumFileName} in the configuration file { .abacus}.
true If the optimum solution of the problem is known and equals the primal bound,
false otherwise.
Opens the file specified with the parameter { OptimumFileName} in the configuration file { .abacus} and tries to find a line with the name of the problem instance (as specified in the constructor of ABA_MASTER) as first string.
true If a line with problemName_ has been found,
false otherwise.
Does nothing but can be redefined in derived classes for output before the timing statistics.
true If cutting has been set to true in the call of the constructor of the class ABA_MASTER, i.e., if cutting planes should be generated in the subproblem optimization.
false otherwise.
Definition at line 1952 of file master.h.
true If pricing has been set to true in the call of the constructor of the class ABA_MASTER, i.e., if a columns should be generated in the subproblem optimization.
false otherwise.
Definition at line 1957 of file master.h.
A pointer to the object holding the optimization sense of the problem.
Definition at line 1917 of file master.h.
A pointer to the object storing the solution history of this branch and cut problem.
Definition at line 1922 of file master.h.
A pointer to the set of open subproblems.
Definition at line 1927 of file master.h.
A pointer to the default pool storing the constraints of the problem formulation.
Definition at line 1937 of file master.h.
A pointer to the default pool for the generated cutting planes.
Definition at line 1942 of file master.h.
A pointer to the default pool storing the variables.
Definition at line 1947 of file master.h.
Can be used to access the root node of the \ tree.
A pointer to the root node of the enumeration tree.
Definition at line 1907 of file master.h.
A pointer to the root of the remaining \ tree, i.e., the subproblem which is an ancestor of all open subproblems and has highest level in the tree.
Definition at line 1912 of file master.h.
The status of the ABA_MASTER.
Definition at line 2141 of file master.h.
A pointer to the name of the instance being optimized (as specified in the constructor of this class).
A pointer to the timer measuring the total wall clock time.
Definition at line 1966 of file master.h.
True, if an approximative solver should be used
Definition at line 1961 of file master.h.
A pointer to the timer measuring the total cpu time for the optimization.
Definition at line 1971 of file master.h.
A pointer to the timer measuring the cpu time spent in members of the LP-interface.
Definition at line 1976 of file master.h.
A pointer to the timer measuring the cpu time required by the LP solver.
Definition at line 1981 of file master.h.
A pointer to the timer measuring the cpu time spent in the separation of cutting planes.
Definition at line 1986 of file master.h.
A pointer to the timer measuring the cpu time spent in the heuristics for the computation of feasible solutions.
Definition at line 1991 of file master.h.
A pointer to the timer measuring the cpu time spent in pricing.
Definition at line 1996 of file master.h.
A pointer to the timer measuring the cpu time spent in finding and selecting the branching rules.
Definition at line 2001 of file master.h.
The number of generated subproblems.
Definition at line 2036 of file master.h.
The number of optimized linear programs (only LP-relaxations).
Definition at line 2041 of file master.h.
The highest level in the tree which has been reached during the implicit enumeration.
Definition at line 2046 of file master.h.
The number of root changes of the remaining \ tree.
Definition at line 2051 of file master.h.
The number of subproblems which have already been selected from the set of open subproblems.
Definition at line 2056 of file master.h.
Writes all parameters of the class ABA_MASTER together with their values to the global output stream.
The branching strategy.
Definition at line 2261 of file master.h.
Changes the branching strategy.
Definition at line 2266 of file master.h.
The Lp Solver.
Definition at line 2271 of file master.h.
Changes the default Lp solver.
Definition at line 2276 of file master.h.
Definition at line 739 of file master.h.
The number of variables that should be tested for the selection of the branching variable.
Definition at line 2281 of file master.h.
This version of the function nbranchingVariableCandidates() sets the number of tested branching variable candidates.
The guarantee specification for the optimization.
Definition at line 2286 of file master.h.
This version of the function requiredGuarantee() changes the guarantee specification.
The maximal depth up to which the enumeration should be performed. By default the maximal enumeration depth is INT .
Definition at line 2291 of file master.h.
This version of the function maxLevel() changes the maximal enumeration depth.
If it is set to 1 the \ algorithm becomes a pure cutting plane algorithm.
The maximal cpu time which can be used by the optimization.
Definition at line 2296 of file master.h.
Sets the maximal usable cpu time for the optimization.
Definition at line 2301 of file master.h.
The function maxCowTime().
The maximal wall-clock time for the optimization.
Definition at line 2306 of file master.h.
This version of the function maxCowTime() set the maximal wall-clock time for the optimization.
Definition at line 2311 of file master.h.
true Then we assume that all feasible solutions have integral objective function values,
false otherwise.
Definition at line 2316 of file master.h.
This version of function objInteger() sets the assumption that the objective function values of all feasible solutions are integer.
Definition at line 2321 of file master.h.
The function tailOffNLp().
The number of linear programs considered in the tailing off analysis.
Definition at line 2326 of file master.h.
Sets the number of linear programs considered in the tailing off analysis.
This new value is only relevant for subproblems activated { after} the change of this value.
Definition at line 2331 of file master.h.
The function tailOffPercent().
The minimal change of the dual bound for the tailing off analysis in percent.
Definition at line 2336 of file master.h.
This version of the function tailOffPercent() sets the minimal change of the dual bound for the tailing off analysis.
This change is only relevant for subproblems activated { after} calling this function.
The output mode.
Definition at line 2341 of file master.h.
The version of the function outLevel() sets the output mode.
Definition at line 2346 of file master.h.
The output mode for the log-file.
Definition at line 2351 of file master.h.
This version of the function logLevel() sets the output mode for the log-file.
Definition at line 2356 of file master.h.
true If the number of optimizations nOpt of a subproblem exceeds the delayed branching threshold,
false otherwise.
Sets the number of optimizations of a subproblem until sons are created in ABA_SUB::branching().
If this value is 0, then a branching step is performed at the end of the subproblem optimization as usually if the subproblem can be fathomed. Otherwise, if this value is strictly positive, the subproblem is put back for a later optimization. This can be advantageous if in the meantime good cutting planes or primal bounds can be generated. The number of times the subproblem is put back without branching is indicated by this value.
Definition at line 2361 of file master.h.
The number of optimizations of a subproblem until sons are created. For further detatails we refer to dbThreshold(int).
Definition at line 2366 of file master.h.
The maximal number of rounds, i.e., number of subproblem optimizations, a subproblem is dormant, i.e., it is not selected from the set of open subproblem if its status is Dormant, if possible.
Definition at line 2371 of file master.h.
Sets the number of rounds a subproblem should stay dormant.
Definition at line 2376 of file master.h.
The mode of the primal bound initialization.
Definition at line 2381 of file master.h.
Sets the mode of the primal bound initialization.
Definition at line 2386 of file master.h.
The number of linear programs being solved between two additional pricing steps. If no additional pricing steps should be executed this parameter has to be set to 0. The default value of the pricing frequency is 0. This parameter does not influence the execution of pricing steps which are required for the correctness of the algorithm.
Definition at line 2391 of file master.h.
This version of the function pricingFreq() sets the number of linear programs being solved between two additional pricing steps.
The frequency of subproblems in which constraints or variables should be generated.
Definition at line 2396 of file master.h.
This version of the function skipFactor() sets the frequency for constraint and variable generation.
This version of the function skippingMode() sets the skipping strategy.
Definition at line 2406 of file master.h.
The skipping strategy.
Definition at line 2401 of file master.h.
The mode for the elimination of constraints.
Definition at line 2191 of file master.h.
Changes the constraint elimination mode.
Definition at line 2196 of file master.h.
The mode for the elimination of variables.
Definition at line 2201 of file master.h.
Changes the variable elimination mode.
Definition at line 2206 of file master.h.
The zero tolerance for the elimination of constraints by the slack criterion.
Definition at line 2211 of file master.h.
Changes the tolerance for the elimination of constraints by the slack criterion.
Definition at line 2216 of file master.h.
The zero tolerance for the elimination of variables by the reduced cost criterion.
Definition at line 2221 of file master.h.
Changes the tolerance for the elimination of variables by the reduced cost criterion.
Definition at line 2226 of file master.h.
The age for the elimination of variables by the reduced cost criterion.
Definition at line 2231 of file master.h.
Changes the age for the elimination of variables by the reduced cost criterion.
Definition at line 2236 of file master.h.
The age for the elimination of constraints.
Definition at line 2241 of file master.h.
Changes the age for the elimination of constraints.
Definition at line 2246 of file master.h.
true Then variables are fixed and set by reduced cost criteria.
false Then no variables are fixed or set by reduced cost criteria.
Definition at line 2061 of file master.h.
Turns fixing and setting variables by reduced cost on or off.
Definition at line 2066 of file master.h.
true Then the linear program is output every iteration of the subproblem optimization.
false The linear program is not output.
Definition at line 2071 of file master.h.
Turns the output of the linear program in every iteration on or off.
Definition at line 2076 of file master.h.
The maximal number of constraints which should be added in every iteration of the cutting plane algorithm.
Definition at line 2081 of file master.h.
Sets the maximal number of constraints that are added in an iteration of the cutting plane algorithm.
Definition at line 2086 of file master.h.
The size of the buffer for generated constraints in the cutting plane algorithm.
Definition at line 2091 of file master.h.
Changes the maximal number of constraints that are buffered in an iteration of the cutting plane algorithm.
This function changes only the default value for subproblems that are activated after its call.
Definition at line 2096 of file master.h.
The maximal number of variables which should be added in the column generation algorithm.
Definition at line 2101 of file master.h.
Changes the maximal number of variables that are added in an iteration of the subproblem optimization.
Definition at line 2106 of file master.h.
The size of the buffer for the variables generated in the column generation algorithm.
Definition at line 2111 of file master.h.
Changes the maximal number of variables that are buffered in an iteration of the subproblem optimization.
This function changes only the default value for subproblems that are activated after its call.
Definition at line 2116 of file master.h.
The maximal number of iterations per subproblem optimization (-1 means no iteration limit).
Definition at line 2121 of file master.h.
Changes the default value for the maximal number of iterations of the optimization of a subproblem.
This function changes only this value for subproblems that are constructed after this function call. For already constructed objects the value can be changed with the function ABA_SUB::maxIterations().
Definition at line 2126 of file master.h.
true Then we try to eliminate fixed and set variables from the linear program.
false Fixed or set variables are not eliminated.
Definition at line 2151 of file master.h.
This version of the function eliminateFixedSet() can be used to turn the elimination of fixed and set variables on or off.
Definition at line 2156 of file master.h.
true Then a new root of the remaining \ tree is reoptimized such that the associated reduced costs can be used for the fixing of variables.
false A new root is not reoptimized.
Definition at line 2161 of file master.h.
Turns the reoptimization of new root nodes of the remaining branch and bound tree on or off.
Definition at line 2166 of file master.h.
The name of the file that stores the optimum solutions.
Definition at line 2131 of file master.h.
Changes the name of the file in which the value of the optimum solution is searched.
Definition at line 2136 of file master.h.
true Then the average distance of the fractional solution from all added cutting planes is output every iteration of the subproblem optimization.
false The average cut distance is not output.
Definition at line 2171 of file master.h.
Turns the output of the average distance of the added cuts from the fractional solution on or off.
Definition at line 2176 of file master.h.
The mode of output for the Vbc-Tool.
Definition at line 2181 of file master.h.
Changes the mode of output for the Vbc-Tool.
This function should only be called before the optimization is started with the function ABA_MASTER::optimize().
Definition at line 2186 of file master.h.
Set solver specific parameters. The default does nothing.
true if an error has occured otherwise
Sets up the default pools for variables, constraints, and cutting planes.
Is overloaded such that also a first set of cutting planes can be inserted into the cutting plane pool.
Can be used to initialize the sense of the optimization in derived classes, if this has not been already performed when the constructor of ABA_MASTER has been called.
Implements the best first search enumeration.
If the bounds of both subproblems are equal, then the subproblems are compared with the function equalSubCompare().
-1 If subproblem s1 has a worse dual bound than s2, i.e., if it has a smaller dual bound for minimization or a larger dual bound for maximization problems.
1 If subproblem s2 has a worse dual bound than s1.
0 If both subproblems have the same priority in the enumeration strategy.
Is called from the function bestFirstSearch() and from the function depthFirstSearch() if the subproblems s1 and s2 have the same priority.
If both subproblems were generated by setting a binary variable, then that subproblem has higher priority of which the branching variable is set to upper bound.
This function can be redefined to resolve equal subproblems according to problem specific criteria. As the root node is compared with itself and has no branching rule, we have to insert the first line of this function.
0 If both subproblems were not generated by setting a variable, or the branching variable of both subproblems is set to the same bound.
1 If the branching variable of the first subproblem ist set to the upper bound.
-1 If the branching variable of the second subproblem ist set to the upper bound.
Implements the depth first search enumeration strategy, i.e., the subproblem with maximum level is selected.
If the level of both subproblems are equal, then the subproblems are compared with the function equalSubCompare().
-1 If subproblem s1 has higher priority,
0 if both subproblems have equal priority,
1 otherwise.
Implements the breadth first search enumeration strategy, i.e., the subproblem with minimum level is selected.
If both subproblems have the same level, the smaller one is the one which has been generated earlier, i.e., the one with the smaller id.
-1 If subproblem s1 has higher priority,
0 if both subproblems have equal priority,
1 otherwise.
Performs depth-first search until a feasible solution is found, then the search process is continued with best-first search.
-1 If subproblem s1 has higher priority,
0 if both subproblems have equal priority,
1 otherwise.
Is only a dummy. This function can be used to initialize parameters of derived classes and to overwrite parameters read from the file { .abacus} by the function ().
Should return a pointer to the first subproblem of the optimization, i.e., the root node of the enumeration tree. This is a pure virtual function since a pointer to a problem specific subproblem should be returned, which is derived from the class ABA_SUB.
The default implementation of initializeOptimization() does nothing.
This virtual function can be used as an entrance point to perform some initializations after optimize() is called.
The default implementation of terminateOptimization() does nothing.
This virtual function can be used as an entrance point after the optimization process is finished.
Reads the parameter-file { .abacus}, which is searched in the directory given by the environment variable ABACUS_DIR, and calls the virtual function initializeParameters() which can initialize parameters of derived classes and overwrite parameters of this class.
All parameters are first inserted together with their values in a parameter table in the function readParameters(). If the virtual dummy function initializeParameters() is redefined in a derived class and also reads a parameter file with the function readParameters(), then already inserted parameters can be overwritten.
After all parameters are input we extract with the function assignParameter() all parameters. Problem specific parameters should be extracted in a redefined version of initializeParameters(). extracted from this table
Initializes the LP solver specific default Parameters if they are not read from the parameter-file { .abacus}.
This function is implemented in the file lpif.cc.
Prints the LP solver specific parameters.
This function is implemented in the file lpif.cc.
Prints the LP solver specific statistics.
This function is implemented in the file lpif.cc.
Returns a pointer to an open subproblem for further processing.
If the set of open subproblems is empty or one of the criteria for early termination of the optimization (maximal cpu time, maximal elapsed time, guarantee) is fulfilled 0 is returned.
Writes the string info to the stream associated with the Tree Interface.
A $ is preceded if the output is written to standard out for further pipelining. If time is true a time string is written in front of the information. The default value of time is true.
Adds the subproblem sub to the stream storing information for graphical output of the enumeration tree if this logging is turned on.
Assigns the color to the subproblem sub in the Tree Interface.
Passes the new lower bound lb to the Tree Interface.
Passes the new upper bound ub to the Tree Interface.
Updates the node information in the node with number id by writing the lower bound lb and the upper bound ub to the node.
Registers a new subproblem which is on level level in enumeration tree.
It is called each time a new subproblem is generated.
Increments the counter for linear programs and should be called in each optimization call of the LP-relaxation.
Definition at line 2006 of file master.h.
Increments the counter of the number of fixed variables by n.
Definition at line 2011 of file master.h.
Increments the counter for the total number of added constraints by n.
Definition at line 2016 of file master.h.
Increments the counter for the total number of removed constraints by n.
Definition at line 2021 of file master.h.
Increments the counter for the total number of added variables by n.
Definition at line 2026 of file master.h.
Increments the counter for the total number of removed variables by n.
Definition at line 2031 of file master.h.
returns a pointer to the object storing the variables which are candidates for being fixed.
Definition at line 1932 of file master.h.
Sets the root of the remaining \ tree to newRoot.
If reoptimize is true a reoptimization of the subproblem *newRoot is performed. This is controlled via a function argument since it might not be desirable when we find a new rRoot_ during the fathoming of a complete subtree ABA_SUB::FathomTheSubtree().
This version of the function status() sets the status of the ABA_MASTER.
Definition at line 2146 of file master.h.
Updates the final dual bound of the root node.
This function should be only called at the end of the root node optimization.
Definition at line 77 of file master.h.
Definition at line 78 of file master.h.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { STATUS[0]=="Optimal"}).
Definition at line 117 of file master.h.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { OUTLEVEL[0]=="Silent"}).
Definition at line 138 of file master.h.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { ENUMSTRAT[0]=="BestFirst"}).
Definition at line 163 of file master.h.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { BRANCHINGSTRAT[0]=="CloseHalf"}).
Definition at line 181 of file master.h.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { PRIMALBOUNDMODE[0]=="None"}).
Definition at line 208 of file master.h.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { SKIPPINGMODE[0]=="None"}).
Definition at line 224 of file master.h.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { CONELIMMODE[0]=="None"}).
Definition at line 240 of file master.h.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { VARELIMMODE[0]=="None"}).
Definition at line 255 of file master.h.
Literal values for the enumerators of the corresponding enumeration type. The order of the enumerators is preserved. (e.g., { VBCMODE[0]=="None"}).
Definition at line 272 of file master.h.
Array for the literal values for possible Osi solvers.
Definition at line 284 of file master.h.
The name of the optimized problem.
Definition at line 1563 of file master.h.
Definition at line 1564 of file master.h.
The sense of the objective function.
Definition at line 1568 of file master.h.
The root node of the enumeration tree.
Definition at line 1572 of file master.h.
The root node of the remaining enumeration tree.
Definition at line 1576 of file master.h.
The set of open subproblems.
Definition at line 1580 of file master.h.
The solution history.
Definition at line 1584 of file master.h.
The enumeration strategy.
Definition at line 1588 of file master.h.
The branching strategy.
Definition at line 1592 of file master.h.
The number of candidates that are evaluated for branching on variables.
Definition at line 1597 of file master.h.
The default LP-Solver.
Definition at line 1601 of file master.h.
Definition at line 1603 of file master.h.
The default pool with the constraints of the problem formulation.
Definition at line 1607 of file master.h.
The default pool of dynamically generated constraints.
Definition at line 1612 of file master.h.
The default pool with the variables of the problem formulation.
Definition at line 1616 of file master.h.
The best known primal bound.
Definition at line 1620 of file master.h.
The best known dual bound.
Definition at line 1624 of file master.h.
The best known dual bound at the end of the optimization of the root node.
Definition at line 1628 of file master.h.
The variables which are candidates for being fixed.
Definition at line 1632 of file master.h.
If true, then constraints are generated in the optimization.
Definition at line 1636 of file master.h.
If true, then variables are generated in the optimization.
Definition at line 1640 of file master.h.
If true, then an approximative solver is used to solve linear programs
Definition at line 1645 of file master.h.
The number of subproblems already selected from the list of open subproblems.
Definition at line 1650 of file master.h.
Ouput for the Tree Interface is generated depending on the value of this variable.
Definition at line 1655 of file master.h.
A pointer to the log stream for the VBC-Tool.
Definition at line 1659 of file master.h.
The guarantee in percent which should be reached when the optimization stops.
If this value is 0.0, then the optimum solution is determined.
Definition at line 1666 of file master.h.
The maximal level in enumeration tree.
Up to this level subproblems are considered in the enumeration.
Definition at line 1672 of file master.h.
The maximal available cpu time.
Definition at line 1676 of file master.h.
The maximal available wall-clock time.
Definition at line 1680 of file master.h.
true, if all objective function values of feasible solutions are assumed to be integer.
Definition at line 1685 of file master.h.
The number of LP-iterations for the tailing off analysis.
Definition at line 1689 of file master.h.
The minimal change of the LP-value on the tailing off analysis.
Definition at line 1693 of file master.h.
The number of optimizations of an ABA_SUB until branching is performed.
Definition at line 1697 of file master.h.
The minimal number of rounds, i.e., number of subproblem optimizations, a subproblem is dormant, i.e., it is not selected from the set of open subproblem if its status is Dormant, if possible.
Definition at line 1703 of file master.h.
The output mode.
Definition at line 1707 of file master.h.
The amount of output written to the log file.
Definition at line 1711 of file master.h.
The mode of the primal bound initialization.
Definition at line 1715 of file master.h.
The number of solved LPs between two additional pricing steps.
Definition at line 1719 of file master.h.
The frequency constraints or variables are generated depending on the skipping mode.
Definition at line 1724 of file master.h.
Either constraints are generated only every skipFactor_ subproblem (SkipByNode) only every skipFactor_ level (SkipByLevel).
Definition at line 1729 of file master.h.
If true, then variables are fixed and set by reduced cost criteria.
Definition at line 1733 of file master.h.
If true, then the linear program is output every iteration.
Definition at line 1737 of file master.h.
The maximal number of added constraints per iteration of the cutting plane algorithm.
Definition at line 1742 of file master.h.
The size of the buffer for generated cutting planes.
Definition at line 1746 of file master.h.
The maximal number of added variables per iteration of the column generation algorithm.
Definition at line 1751 of file master.h.
The size of the buffer for generated variables.
Definition at line 1755 of file master.h.
The maximal number of iterations of the cutting plane/column generation algorithm in the subproblem.
Definition at line 1760 of file master.h.
If true, then nonbasic fixed and set variables are eliminated.
Definition at line 1764 of file master.h.
If true, then an already earlier processed node is reoptimized if it becomes the new root of the remaining \ tree.
Definition at line 1769 of file master.h.
The name of a file storing a list of optimum solutions of problem instances.
Definition at line 1774 of file master.h.
If true then the average distance of the added cutting planes is output every iteration of the cutting plane algorithm.
Definition at line 1779 of file master.h.
The way constraints are automatically eliminated in the cutting plane algorithm.
Definition at line 1784 of file master.h.
The way variables are automatically eliminated in the column generation algorithm.
Definition at line 1789 of file master.h.
The tolerance for the elimination of constraints by the mode NonBinding/.
Definition at line 1794 of file master.h.
The tolerance for the elimination of variables by the mode ReducedCost.
Definition at line 1799 of file master.h.
The number of iterations an elimination criterion must be satisfied until a constraint can be removed.
Definition at line 1804 of file master.h.
The number of iterations an elimination criterion must be satisfied until a variable can be removed.
Definition at line 1809 of file master.h.
The current status of the optimization.
Definition at line 1813 of file master.h.
The timer for the total elapsed time.
Definition at line 1817 of file master.h.
The timer for the total cpu time for the optimization.
Definition at line 1821 of file master.h.
The timer for the cpu time spent in the LP-interface.
Definition at line 1825 of file master.h.
Definition at line 1826 of file master.h.
The timer for the cpu time spent in the separation
Definition at line 1830 of file master.h.
The timer for the cpu time spent in the heuristics for the computation of feasible solutions.
Definition at line 1835 of file master.h.
The timer for the cpu time spent in pricing.
Definition at line 1839 of file master.h.
The timer for the cpu time spent in determining the branching rules.
Definition at line 1843 of file master.h.
The number of generated subproblems.
Definition at line 1847 of file master.h.
The number of solved LPs.
Definition at line 1851 of file master.h.
The highest level which has been reached in the enumeration tree.
Definition at line 1855 of file master.h.
The total number of fixed variables.
Definition at line 1859 of file master.h.
The total number of added constraints.
Definition at line 1863 of file master.h.
The total number of removed constraints.
Definition at line 1867 of file master.h.
The total number of added variables.
Definition at line 1871 of file master.h.
The total number of removed variables.
Definition at line 1875 of file master.h.
The number of changes of the root of the remaining \ tree.
Definition at line 1879 of file master.h.
The documentation for this class was generated from the following file: