| |||||||||

Create a problem with general constraints with logic operators by using the API Description Create a simple problem using the API function problem.addgencons for creating logical (AND and OR) general constraints. Further explanation of this example:
'Xpress Python Reference Manual'
Source Files general_constraints_logic_api.py # Here we use the and/or operators of the Python interface to create a # new optimization problem. # # (C) Fair Isaac Corp., 1983-2020 # Solve a simple SAT problem by finding the solution with the fewest # True variables that satisfy all clauses import xpress as xp p = xp.problem() N = 10 k = 5 x = [xp.var(vartype=xp.binary) for _ in range(N)] p = xp.problem(x) # Creates a continuous list despite the 2 step in range() y_and = [xp.var(vartype=xp.binary) for i in range(0, N-1, 2)] y_or = [xp.var(vartype=xp.binary) for i in range(N-k)] p.addVariable(y_and, y_or) p.addgencons([xp.gencons_and] * (N//2) + [xp.gencons_or] * (N-k), y_and + y_or, # two list of resultants [2*i for i in range(N // 2)] + # colstart is the list [0, 2, 4...] for the AND constraint [2 * (N // 2) + k*i for i in range(N-k)], # ... and then the list [0, k, 2*k...] displaced by 2N x[:2 * (N//2)] + # consider all original variables in this order [x[i+j] for j in range(k) for i in range(N-k)]) # and then variables [0..k-1, 1..k, 2..k+1, ...] # Set time limit to 20 seconds p.controls.maxtime = -20 p.solve() print("solution: x = ", p.getSolution()) | |||||||||

© Copyright 2021 Fair Isaac Corporation. |