Examples with IntDomainMax org.chocosolver.solver.search.strategy.selectors.values.IntDomainMax used on opensource projects

Example 1 with IntDomainMax

use of org.chocosolver.solver.search.strategy.selectors.values.IntDomainMax in project scheduler by btrplace.

the class CMinMigrations method injectPlacementHeuristic.

private void injectPlacementHeuristic(ReconfigurationProblem p, Parameters ps, IntVar cost) {
    List<CShareableResource> rcs = rp.getSourceModel().getViews().stream().filter(v -> v instanceof ShareableResource).map(v -> (CShareableResource) rp.getRequiredView(v.getIdentifier())).collect(Collectors.toList());
    useResources = !rcs.isEmpty();
    Model mo = p.getSourceModel();
    Mapping map = mo.getMapping();
    OnStableNodeFirst schedHeuristic = new OnStableNodeFirst(p);
    // Get the VMs to place
    Set<VM> onBadNodes = new HashSet<>(p.getManageableVMs());
    // Get the VMs that runs and have a pretty low chances to move
    Set<VM> onGoodNodes = map.getRunningVMs(map.getOnlineNodes());
    onGoodNodes.removeAll(onBadNodes);
    List<VMTransition> goodActions = p.getVMActions(onGoodNodes);
    List<VMTransition> badActions = p.getVMActions(onBadNodes);
    Solver s = p.getSolver();
    // Get the VMs to move for exclusion issue
    Set<VM> vmsToExclude = new HashSet<>(p.getManageableVMs());
    for (Iterator<VM> ite = vmsToExclude.iterator(); ite.hasNext(); ) {
        VM vm = ite.next();
        if (!(map.isRunning(vm) && p.getFutureRunningVMs().contains(vm))) {
            ite.remove();
        }
    }
    List<AbstractStrategy<?>> strategies = new ArrayList<>();
    Map<IntVar, VM> pla = VMPlacementUtils.makePlacementMap(p);
    if (!vmsToExclude.isEmpty()) {
        List<VMTransition> actions = new LinkedList<>();
        // Get all the involved slices
        for (VM vm : vmsToExclude) {
            if (p.getFutureRunningVMs().contains(vm)) {
                actions.add(p.getVMAction(vm));
            }
        }
        placeVMs(ps, strategies, actions, schedHeuristic, pla);
    }
    TObjectIntMap<VM> costs = CShareableResource.getWeights(rp, rcs);
    badActions.sort((v2, v1) -> costs.get(v1.getVM()) - costs.get(v2.getVM()));
    goodActions.sort((v2, v1) -> costs.get(v1.getVM()) - costs.get(v2.getVM()));
    placeVMs(ps, strategies, badActions, schedHeuristic, pla);
    placeVMs(ps, strategies, goodActions, schedHeuristic, pla);
    // Reinstantations. Try to reinstantiate first
    List<IntVar> migs = new ArrayList<>();
    for (VMTransition t : rp.getVMActions()) {
        if (t instanceof RelocatableVM) {
            migs.add(((RelocatableVM) t).getRelocationMethod());
        }
    }
    strategies.add(Search.intVarSearch(new FirstFail(rp.getModel()), new IntDomainMax(), migs.toArray(new IntVar[migs.size()])));
    if (!p.getNodeActions().isEmpty()) {
        // Boot some nodes if needed
        IntVar[] starts = p.getNodeActions().stream().map(Transition::getStart).toArray(IntVar[]::new);
        strategies.add(new IntStrategy(starts, new FirstFail(rp.getModel()), new IntDomainMin()));
        // Fix the duration. The side effect will be that states will be fixed as well
        // with the objective to not do un-necessary actions
        IntVar[] durations = p.getNodeActions().stream().map(Transition::getDuration).toArray(IntVar[]::new);
        strategies.add(new IntStrategy(durations, new FirstFail(rp.getModel()), new IntDomainMin()));
    }
    postCostConstraints();
    // /SCHEDULING PROBLEM
    MovementGraph gr = new MovementGraph(rp);
    IntVar[] starts = dSlices(rp.getVMActions()).map(Slice::getStart).filter(v -> !v.isInstantiated()).toArray(IntVar[]::new);
    strategies.add(new IntStrategy(starts, new StartOnLeafNodes(rp, gr), new IntDomainMin()));
    strategies.add(new IntStrategy(schedHeuristic.getScope(), schedHeuristic, new IntDomainMin()));
    IntVar[] ends = rp.getVMActions().stream().map(Transition::getEnd).filter(v -> !v.isInstantiated()).toArray(IntVar[]::new);
    strategies.add(Search.intVarSearch(new MyInputOrder<>(s), new IntDomainMin(), ends));
    // At this stage only it matters to plug the cost constraints
    strategies.add(new IntStrategy(new IntVar[] { p.getEnd(), cost }, new MyInputOrder<>(s, this), new IntDomainMin()));
    s.setSearch(new StrategiesSequencer(s.getEnvironment(), strategies.toArray(new AbstractStrategy[strategies.size()])));
}

Example 2 with IntDomainMax

use of org.chocosolver.solver.search.strategy.selectors.values.IntDomainMax in project scheduler by btrplace.

the class CMinMTTR method injectPlacementHeuristic.

private void injectPlacementHeuristic(ReconfigurationProblem p, Parameters ps, IntVar cost) {
    List<CShareableResource> rcs = rp.getSourceModel().getViews().stream().filter(v -> v instanceof ShareableResource).map(v -> (CShareableResource) rp.getRequiredView(v.getIdentifier())).collect(Collectors.toList());
    useResources = !rcs.isEmpty();
    Model mo = p.getSourceModel();
    Mapping map = mo.getMapping();
    OnStableNodeFirst schedHeuristic = new OnStableNodeFirst(p);
    // Get the VMs to place
    Set<VM> onBadNodes = new HashSet<>(p.getManageableVMs());
    // Get the VMs that runs and have a pretty low chances to move
    Set<VM> onGoodNodes = map.getRunningVMs(map.getOnlineNodes());
    onGoodNodes.removeAll(onBadNodes);
    List<VMTransition> goodActions = p.getVMActions(onGoodNodes);
    List<VMTransition> badActions = p.getVMActions(onBadNodes);
    Solver s = p.getSolver();
    // Get the VMs to move for exclusion issue
    Set<VM> vmsToExclude = new HashSet<>(p.getManageableVMs());
    for (Iterator<VM> ite = vmsToExclude.iterator(); ite.hasNext(); ) {
        VM vm = ite.next();
        if (!(map.isRunning(vm) && p.getFutureRunningVMs().contains(vm))) {
            ite.remove();
        }
    }
    List<AbstractStrategy<?>> strategies = new ArrayList<>();
    Map<IntVar, VM> pla = VMPlacementUtils.makePlacementMap(p);
    if (!vmsToExclude.isEmpty()) {
        List<VMTransition> actions = new LinkedList<>();
        // Get all the involved slices
        for (VM vm : vmsToExclude) {
            if (p.getFutureRunningVMs().contains(vm)) {
                actions.add(p.getVMAction(vm));
            }
        }
        placeVMs(ps, strategies, actions, schedHeuristic, pla);
    }
    TObjectIntMap<VM> costs = CShareableResource.getWeights(rp, rcs);
    badActions.sort((v2, v1) -> costs.get(v1.getVM()) - costs.get(v2.getVM()));
    goodActions.sort((v2, v1) -> costs.get(v1.getVM()) - costs.get(v2.getVM()));
    placeVMs(ps, strategies, badActions, schedHeuristic, pla);
    placeVMs(ps, strategies, goodActions, schedHeuristic, pla);
    // Reinstantations. Try to reinstantiate first
    List<IntVar> migs = new ArrayList<>();
    for (VMTransition t : rp.getVMActions()) {
        if (t instanceof RelocatableVM) {
            migs.add(((RelocatableVM) t).getRelocationMethod());
        }
    }
    strategies.add(Search.intVarSearch(new FirstFail(rp.getModel()), new IntDomainMax(), migs.toArray(new IntVar[migs.size()])));
    if (!p.getNodeActions().isEmpty()) {
        // Boot some nodes if needed
        IntVar[] starts = p.getNodeActions().stream().map(Transition::getStart).toArray(IntVar[]::new);
        strategies.add(new IntStrategy(starts, new FirstFail(rp.getModel()), new IntDomainMin()));
    }
    // /SCHEDULING PROBLEM
    MovementGraph gr = new MovementGraph(rp);
    IntVar[] starts = dSlices(rp.getVMActions()).map(Slice::getStart).filter(v -> !v.isInstantiated()).toArray(IntVar[]::new);
    strategies.add(new IntStrategy(starts, new StartOnLeafNodes(rp, gr), new IntDomainMin()));
    strategies.add(new IntStrategy(schedHeuristic.getScope(), schedHeuristic, new IntDomainMin()));
    IntVar[] ends = rp.getVMActions().stream().map(Transition::getEnd).filter(v -> !v.isInstantiated()).toArray(IntVar[]::new);
    strategies.add(Search.intVarSearch(new MyInputOrder<>(s), new IntDomainMin(), ends));
    // At this stage only it matters to plug the cost constraints
    strategies.add(new IntStrategy(new IntVar[] { p.getEnd(), cost }, new MyInputOrder<>(s, this), new IntDomainMin()));
    s.setSearch(new StrategiesSequencer(s.getEnvironment(), strategies.toArray(new AbstractStrategy[strategies.size()])));
}