Update OR-Tools to v9.1

This update, despite ostensibly being a minor version, includes breaking
changes that must be accounted for.

Overflow is much more strictly checked, so the magnitude of certain
constants has been decreased.

CP-SAT's default number of workers has been changed to reflect the
default of this script. As such, the script no longer needs to change
that parameter unless a specific number of workers has been specified.

In light of the breaking changes, the OR-Tools version is now pinned at
9.1 instead of being permitted to use future minor versions.

Pipfile

@@ -4,7 +4,7 @@ verify_ssl = true
 name = "pypi"
 
 [packages]
-ortools = "~=9.0"
+ortools = "9.1"
 windows-curses = {platform_system = "== 'Windows'"}
 
 [scripts]

bonemarketsolver/objects/bone_market_model.py

@@ -28,7 +28,7 @@ Each parameter is interpreted as a BoundedLinearExpression, and a layer of indir
 Each parameter is interpreted as a BoundedLinearExpression, and a layer of indirection is applied such that each Constraint in the returned tuple can accept an enforcement literal."""
         intermediate_target, target_constraint = self.NewIntermediateIntVar(target, f'{repr(target)} == {repr(num)} // {repr(denom)}: target')
         intermediate_num, num_constraint = self.NewIntermediateIntVar(num, f'{repr(target)} == {repr(num)} // {repr(denom)}: num', lb = 0)
-        intermediate_denom, denom_constraint = self.NewIntermediateIntVar(denom, f'{repr(target)} == {repr(num)} // {repr(denom)}: denom', lb = 0)
+        intermediate_denom, denom_constraint = self.NewIntermediateIntVar(denom, f'{repr(target)} == {repr(num)} // {repr(denom)}: denom', lb = 1)
 
         super().AddDivisionEquality(intermediate_target, intermediate_num, intermediate_denom)
         return (target_constraint, num_constraint, denom_constraint)
@@ -41,7 +41,7 @@ Each parameter is interpreted as a BoundedLinearExpression, and a layer of indir
 `multiple` defaults to the same value as `denom` if unspecified."""
         quotient = self.NewIntVar(f'{repr(target)} == ({repr(num)} // {repr(denom)}) * {repr(multiple)}: quotient')
         intermediate_num, num_constraint = self.NewIntermediateIntVar(num, f'{repr(target)} == ({repr(num)} // {repr(denom)}) * {repr(multiple)}: num', lb = 0)
-        intermediate_denom, denom_constraint = self.NewIntermediateIntVar(denom, f'{repr(target)} == ({repr(num)} // {repr(denom)}) * {repr(multiple)}: denom', lb = 0)
+        intermediate_denom, denom_constraint = self.NewIntermediateIntVar(denom, f'{repr(target)} == ({repr(num)} // {repr(denom)}) * {repr(multiple)}: denom', lb = 1)
         intermediate_target, target_constraint = self.NewIntermediateIntVar(target, f'{repr(target)} == ({repr(num)} // {repr(denom)}) * {repr(multiple)}: target')
         if multiple:
             intermediate_multiple, multiple_constraint = self.NewIntermediateIntVar(multiple, f'{repr(target)} == ({repr(num)} // {repr(denom)}) * {repr(multiple)}: multiple')
@@ -110,7 +110,7 @@ Each parameter is interpreted as a BoundedLinearExpression, and a layer of indir
         self.AddLinearExpressionInDomain(linear_exp, domain.Complement()).OnlyEnforceIf(intermediate.Not())
         return intermediate
 
-    def NewIntermediateIntVar(self, linear_exp, name, *, lb = cp_model.INT_MIN//8, ub = cp_model.INT_MAX//8):
+    def NewIntermediateIntVar(self, linear_exp, name, *, lb = cp_model.INT32_MIN, ub = cp_model.INT32_MAX):
         """Creates an integer variable equivalent to the given expression and returns a tuple consisting of the variable and constraint for use with enforcement literals."""
 
         intermediate = super().NewIntVar(lb, ub, name)

bonemarketsolver/solve.py

@@ -4,7 +4,6 @@ __all__ = ['Adjustment', 'Appendage', 'Buyer', 'Declaration', 'DiplomatFascinati
 __author__ = "Jeremy Saklad"
 
 from functools import partialmethod
-from os import cpu_count
 
 from ortools.sat.python import cp_model
 
@@ -22,7 +21,7 @@ from .data.torsos import Torso
 from .objects.bone_market_model import BoneMarketModel
 
 # This multiplier is applied to the profit margin to avoid losing precision due to rounding.
-PROFIT_MARGIN_MULTIPLIER = 10000000
+PROFIT_MARGIN_MULTIPLIER = 10000
 
 # This is the highest number of attribute to calculate fractional exponents for.
 MAXIMUM_ATTRIBUTE = 100
@@ -31,7 +30,7 @@ MAXIMUM_ATTRIBUTE = 100
 DIFFICULTY_SCALER = 0.6
 
 
-def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = None, occasional_buyer = None, diplomat_fascination = None, desired_buyers = [], maximum_cost = cp_model.INT32_MAX, maximum_exhaustion = cp_model.INT32_MAX, time_limit = float('inf'), workers = cpu_count(), blacklist = [], stdscr = None):
+def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = None, occasional_buyer = None, diplomat_fascination = None, desired_buyers = [], maximum_cost = cp_model.INT32_MAX, maximum_exhaustion = cp_model.INT32_MAX, time_limit = float('inf'), workers = None, blacklist = [], stdscr = None):
     model = BoneMarketModel()
 
     actions = {}
@@ -1202,6 +1201,7 @@ Exhaustion: {solver.Value(exhaustion):n}"""
     printer = SkeletonPrinter()
 
     solver = cp_model.CpSolver()
+    if workers:
         solver.parameters.num_search_workers = workers
     solver.parameters.max_time_in_seconds = time_limit
 
@@ -1210,7 +1210,7 @@ Exhaustion: {solver.Value(exhaustion):n}"""
         solver.parameters.log_search_progress = True
         solver.Solve(model)
     else:
-        solver.SolveWithSolutionCallback(model, printer)
+        solver.Solve(model, printer)
 
     status = solver.StatusName()