Use itertools#25
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Pull request overview
This PR refactors several deeply nested iteration patterns in the SCIP ILP scheduler to use itertools.product, aiming to simplify the code and reduce indentation depth in the scheduler model construction and solution-dumping logic.
Changes:
- Replace multiple nested
forloops withitertools.product(...)across variable creation and constraint generation. - Refactor the solution-dump loops to use
product(...)for iterating over(x, y, t, c).
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| for p in range(P): | ||
| for t in range(T): | ||
| enterc[i, j, p, t] = m.addVar( | ||
| vtype="B", name=f"enterc_{i}_{j}_{p}_{t}" | ||
| ) | ||
| exitc[i, j, p, t] = m.addVar( | ||
| vtype="B", name=f"exitc_{i}_{j}_{p}_{t}" | ||
| ) |
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| for x, y, t, c in product(range(Nx), range(Ny), range(T), range(C)): | ||
| enterLine = "enter[%d][%d][%d][%d][%d] = %d" % ( | ||
| x, | ||
| y, | ||
| c, |
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