Examples of Solver

choco.kernel.solver.Solver
com.cloudera.oryx.common.math.Solver
Encapsulates a {@link DecompositionSolver} from Commons Math.
com.hpctoday.fada.integersolver.Solver
driftingdroids.model.Solver
hu.u_szeged.nbo.res_alloc.main.Solver
jinngine.physics.solver.Solver
Solver for a non-linear complimentarity problem (NCP).
The contact force problem generated by Jinngine is ultimately a non-linear complementarity problem. In fact, when disregarding the coupling between friction forces and normal forces, the problem becomes a mixed linear complimentarity problem, or MLCP for short. The MLCP is on the form
Given the matrix A, the vector b, and the solution limit vectors l and u, Find x, such that
w = A x + b
where
if x_i=u_i then w_i<=0
if x_i in (l_i,u_i) then w_i = 0
if x_i=l_i then w_i>=0
A is the matrix J M^(-1) J^T which describes constraint relations, and b is the vector of desired change in velocities.
This problem class can model normal-component contact forces and various joint types. The reason why this becomes a NCP when contact friction is introduced, is that we allow u and l to depend on the magnitude of some x_i vales, namely the x_i's that represent normal contact forces, so
l_i = -|mu * x_j| and u_i = |mu*x_j|
where i is the index of a friction constraint, j is the index of the normal force, and mu is the friction coefficient. constraint to which the friction constraint is coupled. This coupling is done to model an approximation to Coulomb's law of friction.
kodkod.engine.Solver
A computational engine for solving relational formulae. A {@link kodkod.ast.Formula formula} is solved with respect to given {@link kodkod.instance.Bounds bounds} and {@link kodkod.engine.config.Options options}. @specfield options: Options @author Emina Torlak
net.myrrix.common.math.Solver
A solver for the system Ax = b, where A is an n x n matrix and x and b are n-element vectors. An implementation of this class encapsulates a solver which implicitly contains A. @author Sean Owen @since 1.0
net.sf.cpsolver.ifs.solver.Solver
net.sf.javailp.Solver
org.boblycat.abbots.Solver
org.drools.planner.core.Solver
A Solver solves planning problems.
Most methods are not thread-safe and should be called from the same thread.
org.drools.solver.core.Solver
org.jakstab.solver.Solver
A generic interface to SMT solvers, represents a logical context that can be updated with assertions and checked for satisfiability. @author Johannes Kinder
org.moxie.Solver
Solves transitive dependency chains, scoped classpaths, and linked projects.
Solver employs Maven 2 transitive dependency resolution based on "nearness" and declaration order using a 2-pass scheme. Pass one recursively retrieves all referenced POMs. Pass two analyzes each retrieved POM for a particular solving scope and builds a flat dependency list with ring scores.
Ring-0 is the project itself. Ring-1 are direct named dependencies. Ring > 1 are solved transitive dependencies. Dependency conflicts are resolved by choosing the dependency in the lowest ring OR the first declaration, if the rings are equal.
Linked projects are treated as source folders of the build project. Therefore the dependencies linked projects are assimilated into the build project's dependencies.
org.optaplanner.core.api.solver.Solver
A Solver solves a planning problem. Clients usually call {@link #solve(Solution)} and then {@link #getBestSolution()}.
These methods are not thread-safe and should be called from the same thread, except for the methods that are explicitly marked as thread-safe. Note that despite that {@link #solve(Solution)} is not thread-safe for clients of this class,that method is free to do multi-threading inside itself.
Build by a {@link SolverFactory}.
solver.Solver
The Solver is the header component of Constraint Programming. It embeds the list of Variable (and their Domain), the Constraint's network, and a IPropagationEngine to pilot the propagation.
Solver includes a AbstractSearchLoop to guide the search loop: apply decisions and propagate, run backups and rollbacks and store solutions. @author Xavier Lorca @author Charles Prud'homme @version 0.01, june 2010 @see solver.variables.Variable @see solver.constraints.Constraint @since 0.01
solvers.Solver
class to represent a solver * @author Hélène Collavizza @date June 2008

Examples of solver.Solver


    BoolVar[][][] P, M;


    @Override
    public void createSolver() {
        solver = new Solver("Social golfer " + g + "-" + w + "-" + s);
    }

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Examples of solver.Solver

    int n = 4;
    int vals = n - 1;


    @Override
    public void createSolver() {
        solver = new Solver();
    }

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Examples of solver.Solver

    int n = 10;
    IntVar[] vars;


    @Override
    public void createSolver() {
        solver = new Solver("Pigeons");
    }

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Examples of solver.Solver

    int n = 4;
    int vals = n - 1;


    @Override
    public void createSolver() {
        solver = new Solver();
    }

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Examples of solver.Solver

  // METHODS
  //***********************************************************************************


  @Override
  public void createSolver() {
    solver = new Solver("Cumulative example: makespan minimisation");
  }

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Examples of solver.Solver

    private final int n = 9;
    IntVar[][] rows, cols, carres;


    @Override
    public void createSolver() {
        solver = new Solver("Sudoku");
    }

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Examples of solver.Solver

    IntVar[] square1, square2, vars;
    Constraint[] ALLDIFFS;


    @Override
    public void createSolver() {
        solver = new Solver("Ortho Latin square " + m);
    }

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Examples of solver.Solver

    Constraint[] lights;
    Constraint alldiff;


    @Override
    public void createSolver() {
        solver = new Solver("Langford number");
    }

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Examples of solver.Solver


    IntVar[] vars;


    @Override
    public void createSolver() {
        solver = new Solver("Eq5");
    }

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Examples of solver.Solver

   * @param val
   * @return la liste des positions des reines.
   */
  public static List<Integer> dominationQueen(int n, int val) {
    System.out.println("Domination queen (Q" + n + ":" + val + ")");
    Solver pb = new Solver("Introductive Example");
    IntVar[] X = new IntVar[n * n];
    //une variable par case avec pour domaine la reine qui l attaque. (les reines sont ainsi designees par les valeurs, et les cases par les variables)
    for (int i = 0; i < X.length; i++) {
      X[i] = VariableFactory.enumerated("Q" + i, 1, n*n, pb);
    }
    IntVar N = VariableFactory.fixed(val,pb);
    pb.post(IntConstraintFactory.nvalues(X,N));
    //i appartient a la variable j ssi la case i est sur une ligne/colonne/diagonale de j
    for (int i = 1; i <= n; i++) {
      for (int j = 1; j <= n; j++) {
        //pour chaque case
        for (int k = 1; k <= n; k++) {
          for (int l = 1; l <= n; l++) {
            if (!(k == i || l == j || Math.abs(i - k) == Math.abs(j - l))) {
              pb.post(IntConstraintFactory.arithm(X[n * (i - 1) + j - 1], "!=", (k - 1) * n + l));
            }
          }
        }
      }
    }


    pb.set(IntStrategyFactory.lexico_LB(X));


    pb.findSolution();
    System.out.println("Back  : " + pb.getMeasures().getBackTrackCount());
    System.out.println("Time  : " + pb.getMeasures().getTimeCount()+" (sec)");


    List<Integer> values = new LinkedList<Integer>();
    if (pb.isFeasible() == ESat.TRUE) {
      for (int i = 0; i < n * n; i++) {
        if (!values.contains(X[i].getValue()))
          values.add(X[i].getValue());
      }
      System.out.print("Solution: ");

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