linear-programming

问题 I've been using PuLP to solve a particular mixed integer linear program (MIP) I am interested in. However, as the problem size grows, PuLP is taking too long. I want to be able to run the solver for some time and terminate it prematurely if its taking to long and obtain the best feasible solution so-far computed. I have tried manually timing the solver out with signal, but the variables are all "None". I've looked at the documentation and PuLP does not seem to support this, though as I

问题 I'm using DOCPLEX to build up a Mixed Integer Linear Programming (MILP) problem which is then solved via CPLEX on Python. However, upon trying to solve the MILP problem using IF-THEN constraints, I receive the following error: DOcplexException: Model.if_then(), nbBus40 >= 3.0 is not discrete This is happening because I have declared nbbus40 variable to be continuous , as shown in the code below: from docplex.mp.model import Model mdl = Model(name='buses') nbbus40 = mdl.continuous_var(name=

问题 I'm using DOCPLEX to build up a Mixed Integer Linear Programming (MILP) problem which is then solved via CPLEX on Python. However, upon trying to solve the MILP problem using IF-THEN constraints, I receive the following error: DOcplexException: Model.if_then(), nbBus40 >= 3.0 is not discrete This is happening because I have declared nbbus40 variable to be continuous , as shown in the code below: from docplex.mp.model import Model mdl = Model(name='buses') nbbus40 = mdl.continuous_var(name=

问题 I have some Pyomo code (see below) which produces one possible solution to the linear equation: 3a + 2b + 2c = 15 Where: -20 <= a <= 0 0 <= b <= 20 20 <= c <= 50 a, b, c are real numbers How could I rewrite the program to produce a random solution every time it is run? I am open to using Pulp as well. My Code: # Coefficients coeffs = [3,2,2] y_target = 15 # Define model and variables model = ConcreteModel() model.a = Var(bounds=(-20,0)) model.b = Var(bounds=(0,20)) model.c = Var(bounds=(20,50

问题 I am a beginner in gurobipy. I would like to add an inverted indicator constraint. Indicator constraint is nothing but depending on a binary variable a constraint does or does not hold. In gurobipy this is written as model.addConstr((x == 1) >> (y + z <= 5)) where x is a binary variable, y and z are integer variables. This statement says that if x is True then the constraint y+z <= 5 holds. But I would like to have an inverted constraint like this. If y+z <= 5 then x == 1. But gurobi does not

问题 I have the next LP problem Maximize 1000 x1 + 500 x2 - 500 x5 - 250 x6 Subject To c1: x1 + x2 - x3 - x4 = 0 c2: - x3 + x5 = 0 c3: - x4 + x6 = 0 With these Bounds 0 <= x1 <= 10 0 <= x2 <= 15 0 <= x5 <= 15 0 <= x6 <= 5 By solving this problem with Cplex dual algorithm I get an optimal solution of 6250. But checking the reduced costs of the variables I get the next results Variable value reduced cost 1 10.0 500.0 1 0.0 -0.0 2 5.0 -0.0 3 5.0 -0.0 4 5.0 -0.0 5 5.0 250.0 Is it possible to have a

问题 I have the next LP problem Maximize 1000 x1 + 500 x2 - 500 x5 - 250 x6 Subject To c1: x1 + x2 - x3 - x4 = 0 c2: - x3 + x5 = 0 c3: - x4 + x6 = 0 With these Bounds 0 <= x1 <= 10 0 <= x2 <= 15 0 <= x5 <= 15 0 <= x6 <= 5 By solving this problem with Cplex dual algorithm I get an optimal solution of 6250. But checking the reduced costs of the variables I get the next results Variable value reduced cost 1 10.0 500.0 1 0.0 -0.0 2 5.0 -0.0 3 5.0 -0.0 4 5.0 -0.0 5 5.0 250.0 Is it possible to have a

问题 I'm trying to code up a simple Simplex algorithm, the first step of which is to find a basic feasible solution: Choose a set B of linearly independent columns of A Set all components of x corresponding to the columns not in B to zero. Solve the m resulting equations to determine the components of x. These are the basic variables. I know the solution will involve using scipy.linalg.svd (or scipy.linalg.lu ) and some numpy.argwhere / numpy.where magic, but I'm not sure exactly how. Does anyone

问题 After 3 days, I can't get a python program packaged into a .exe file. I've tried py2exe (which continuously missed modules), and PyInstaller. Here's the complicated part. My program uses a lot of additional installed modules (coopr, pyomo, openpyxl, glpk, cbc, pyutilib, numpy, etc.). These in turn import all kinds of other things, and I can't track it down (the PyInstaller warning log lists 676 lines of missing or potentially unneeded modules.) However, I've gotten (by adding imports of

问题 After 3 days, I can't get a python program packaged into a .exe file. I've tried py2exe (which continuously missed modules), and PyInstaller. Here's the complicated part. My program uses a lot of additional installed modules (coopr, pyomo, openpyxl, glpk, cbc, pyutilib, numpy, etc.). These in turn import all kinds of other things, and I can't track it down (the PyInstaller warning log lists 676 lines of missing or potentially unneeded modules.) However, I've gotten (by adding imports of