Create a problem with logical constraints
Create a simple problem using the modelling methods max for creating general constraints.
Further explanation of this example: 'Xpress Python Reference Manual'
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# Here we use the and/or operators of the Python interface to create a # new optimization problem. # # (C) Fair Isaac Corp., 1983-2021 # 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)] # At most one of each pair can be True con0 = [(x[i] & x[i+1]) == 0 for i in range(0, N-1, 2)] # At least a quarter of all OR clauses on continuous groups of k # clauses must be True con1 = xp.Sum(xp.Or(*(x[i:i+k])) for i in range(N-k)) >= N/4 p = xp.problem(x, con0, con1) # Set time limit to 20 seconds p.controls.maxtime = -20 p.solve() print("solution: x = ", p.getSolution())
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