Python gurobipy.LinExpr() Examples
The following are 6
code examples of gurobipy.LinExpr().
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Example #1
Source File: statistics.py From msppy with BSD 3-Clause "New" or "Revised" License | 8 votes |
def fit(array, convex=1): """Fit a smooth line to the given time-series data""" N = len(array) m = gurobipy.Model() fv = m.addVars(N) if convex == 1: m.addConstrs(fv[i] <= fv[i-1] for i in range(1,N)) m.addConstrs(fv[i] + fv[i-2] >= 2*fv[i-1] for i in range(2,N)) else: m.addConstrs(fv[i] >= fv[i-1] for i in range(1,N)) m.addConstrs(fv[i] + fv[i-2] <= 2*fv[i-1] for i in range(2,N)) m.setObjective( gurobipy.quicksum([fv[i] * fv[i] for i in range(N)]) - 2 * gurobipy.LinExpr(array,fv.values()) ) m.Params.outputFlag = 0 m.optimize() return [fv[i].X for i in range(N)]
Example #2
Source File: solvers.py From MatchingMarkets.py with BSD 3-Clause "New" or "Revised" License | 5 votes |
def addConstraint(self, constraint, name = None): if not isinstance(constraint, LpConstraint): raise TypeError("Can only add LpConstraint objects") if name: constraint.name = name try: if constraint.name: name = constraint.name else: name = self.unusedConstraintName() except AttributeError: raise TypeError("Can only add LpConstraint objects") #if self._addVariables(constraint.keys()): #self.gurobi_model.update() expr = gurobipy.LinExpr(constraint.values(), [v.solver_var for v in constraint.keys()]) # Solver_var is added inside addVariable if constraint.sense == LpConstraintLE: relation = gurobipy.GRB.LESS_EQUAL elif constraint.sense == LpConstraintGE: relation = gurobipy.GRB.GREATER_EQUAL elif constraint.sense == LpConstraintEQ: relation = gurobipy.GRB.EQUAL else: raise PulpSolverError('Detected an invalid constraint type') self.gurobi_model.addConstr(expr, relation, -constraint.constant, name)
Example #3
Source File: sp.py From msppy with BSD 3-Clause "New" or "Revised" License | 5 votes |
def _add_cut(self, rhs, gradient): temp = gurobipy.LinExpr(gradient, self.states) self.cuts.append( self._model.addConstr( self.modelSense * (self.alpha - temp - rhs) >= 0 ) ) self._model.update()
Example #4
Source File: solvers.py From MatchingMarkets.py with BSD 3-Clause "New" or "Revised" License | 4 votes |
def buildSolverModel(self, lp): """ Takes the pulp lp model and translates it into a gurobi model """ log.debug("create the gurobi model") lp.solverModel = gurobipy.Model(lp.name) log.debug("set the sense of the problem") if lp.sense == LpMaximize: lp.solverModel.setAttr("ModelSense", -1) if self.timeLimit: lp.solverModel.setParam("TimeLimit", self.timeLimit) if self.epgap: lp.solverModel.setParam("MIPGap", self.epgap) log.debug("add the variables to the problem") for var in lp.variables(): lowBound = var.lowBound if lowBound is None: lowBound = -gurobipy.GRB.INFINITY upBound = var.upBound if upBound is None: upBound = gurobipy.GRB.INFINITY obj = lp.objective.get(var, 0.0) varType = gurobipy.GRB.CONTINUOUS if var.cat == LpInteger and self.mip: varType = gurobipy.GRB.INTEGER var.solverVar = lp.solverModel.addVar(lowBound, upBound, vtype = varType, obj = obj, name = var.name) lp.solverModel.update() log.debug("add the Constraints to the problem") for name,constraint in lp.constraints.items(): #build the expression expr = gurobipy.LinExpr(list(constraint.values()), [v.solverVar for v in constraint.keys()]) if constraint.sense == LpConstraintLE: relation = gurobipy.GRB.LESS_EQUAL elif constraint.sense == LpConstraintGE: relation = gurobipy.GRB.GREATER_EQUAL elif constraint.sense == LpConstraintEQ: relation = gurobipy.GRB.EQUAL else: raise PulpSolverError('Detected an invalid constraint type') constraint.solverConstraint = lp.solverModel.addConstr(expr, relation, -constraint.constant, name) lp.solverModel.update()
Example #5
Source File: msp.py From msppy with BSD 3-Clause "New" or "Revised" License | 4 votes |
def read_cuts(self, path): """Read all cuts from csv files. csv files takes the form of: x.varName | y.varName | rhs a | b | c which specifies cut: alpha + ax + by >= c in minimization problem alpha + ax + by <= c in maximization problem Parameters ---------- path: string The location to read csv files """ self._update() for t in range(self.T - 1): m = self.models[t] if type(m) != list: coeffs = pandas.read_csv( path + "{}.csv".format(t), index_col=0 ).values for coeff in coeffs: m.addConstr( ( m.alpha + gurobipy.LinExpr(coeff[:-1], m.states) - coeff[-1] ) * m.modelsense >= 0 ) m.update() else: for k, m in enumerate(m): coeffs = pandas.read_csv( path + "{}_{}.csv".format(t, k), index_col=0 ).values for coeff in coeffs: m.addConstr( ( m.alpha + gurobipy.LinExpr(coeff[:-1], m.states) - coeff[-1] ) * m.modelsense >= 0 ) m.update()
Example #6
Source File: gurobi.py From GridCal with GNU General Public License v3.0 | 4 votes |
def buildSolverModel(self, lp): """ Takes the pulp lp model and translates it into a gurobi model """ log.debug("create the gurobi model") lp.solverModel = gurobipy.Model(lp.name) log.debug("set the sense of the problem") if lp.sense == LpMaximize: lp.solverModel.setAttr("ModelSense", -1) if self.timeLimit: lp.solverModel.setParam("TimeLimit", self.timeLimit) if self.epgap: lp.solverModel.setParam("MIPGap", self.epgap) log.debug("add the variables to the problem") for var in lp.variables(): lowBound = var.lowBound if lowBound is None: lowBound = -gurobipy.GRB.INFINITY upBound = var.upBound if upBound is None: upBound = gurobipy.GRB.INFINITY obj = lp.objective.get(var, 0.0) varType = gurobipy.GRB.CONTINUOUS if var.cat == LpInteger and self.mip: varType = gurobipy.GRB.INTEGER var.solverVar = lp.solverModel.addVar(lowBound, upBound, vtype=varType, obj=obj, name=var.name) lp.solverModel.update() log.debug("add the Constraints to the problem") for name, constraint in lp.constraints.items(): # build the expression expr = gurobipy.LinExpr(list(constraint.values()), [v.solverVar for v in constraint.keys()]) if constraint.sense == LpConstraintLE: relation = gurobipy.GRB.LESS_EQUAL elif constraint.sense == LpConstraintGE: relation = gurobipy.GRB.GREATER_EQUAL elif constraint.sense == LpConstraintEQ: relation = gurobipy.GRB.EQUAL else: raise PulpSolverError('Detected an invalid constraint type') constraint.solverConstraint = lp.solverModel.addConstr(expr, relation, -constraint.constant, name) lp.solverModel.update()