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modify the sandbox to get it more closer to the actual impl

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This commit is contained in:
Adrian Manteza 2022-03-14 18:47:28 +00:00
parent ff9d9b3d49
commit ddb8efc79f
1 changed files with 20 additions and 14 deletions
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34
app/services/solver_sandbox.py
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@ -61,27 +61,26 @@ class SolverSandbox:
break break
def yas_elastic(tif_target = 140.0): # 140 is the optimal def yas_elastic(tif_target = 140.0): # 140 is the optimal
Items = [1,2,3,4,5] Items = [1,2,3,4,5]
Bundles = [1,2]
# For TIF target # For TIF target
tif = { tif = {
1: 10, 1: 10,
2: 20, 2: 20
3: 40,
4: 60,
5: 80
} }
iif = { iif = {
1: 10, 1: 10,
2: 20, 2: 20,
3: 30, 3: 30,
4: 50, 4: 40,
5: 70 5: 50
} }
# --- # ---
items = LpVariable.dicts('Item', Items, cat='Binary') items = LpVariable.dicts('Item', Items, cat='Binary')
bundles = LpVariable.dicts('Bundle', Bundles, cat='Binary')
drift = 0 drift = 0
max_drift = 10 # 10% elasticity max_drift = 10 # 10% elasticity
@ -91,20 +90,27 @@ class SolverSandbox:
problem = LpProblem('TIF_TCC', LpMinimize) problem = LpProblem('TIF_TCC', LpMinimize)
# objective function # objective function
problem += lpSum([(tif[i] + iif[i]) * items[i] for i in Items]) problem += lpSum([items[i] for i in Items])
# Constraint 1 # Constraint 1
problem += lpSum([items[i] for i in Items]) == 3, 'TotalItems' problem += lpSum([items[i] for i in Items] + [bundles[b] for b in Bundles]) == 2, 'TotalItems'
print(f"Calculating TIF target of {tif_target} with drift of {drift}%") print(f"Calculating TIF target of {tif_target} with drift of {drift}%")
# Our own "Elastic Constraints" # Our own "Elastic Constraints"
problem += lpSum( problem += lpSum(
[(tif[i] + iif[i]) * items[i] for i in Items] [iif[i] * items[i] for i in Items]
) >= tif_target - (tif_target * drift_percent), 'TifIifMin' ) >= tif_target - (tif_target * drift_percent), 'ItemIifMin'
problem += lpSum( problem += lpSum(
[(tif[i] + iif[i]) * items[i] for i in Items] [iif[i] * items[i] for i in Items]
) <= tif_target + (tif_target * drift_percent), 'TifIifMax' ) <= tif_target + (tif_target * drift_percent), 'ItemIifMax'
problem += lpSum(
[tif[i] * bundles[i] for i in Bundles]
) >= tif_target - (tif_target * drift_percent), 'BundleTifMin'
problem += lpSum(
[tif[i] * bundles[i] for i in Bundles]
) <= tif_target + (tif_target * drift_percent), 'BundleTifMax'
problem.solve() problem.solve()