private void CreateFoodModel()
{
// avoid trivial constraints
if (!FoodChoices.Any())
{
return;
}
Model.AddConstraint(Expression.Sum(FoodChoices.Select(x => food[x])) <= 1, "use one food only");
foreach (var itm in FoodChoices)
{
var fd = itm.Food;
var fv = food[itm];
// SIMPLIFICATION: no one cares about nq food.
foreach (var prm in fd.Parameters)
{
var bp = prm.BaseParam;
if (!RelevantStats.Contains(bp))
{
continue;
}
var pvals = prm.Values.Where(v => v.Type == ParameterType.Hq).ToList();
// easy case, these just behave like normal gear
// ASSUMPTION: each food provides either a fixed or relative buff for a given base param
foreach (var pval in pvals.OfType <ParameterValueFixed>())
{
FoodExprs.AddExprToDict(bp, pval.Amount * fv);
}
foreach (var pval in pvals.OfType <ParameterValueRelative>())
{
// add relative modifier stat[bp]
Model.AddConstraint(foodcap[itm, bp] <= pval.Amount * stat[bp],
$"relative modifier for food {fd} in slot {bp}");
var limited = pval as ParameterValueRelativeLimited;
if (limited != null)
{
Model.AddConstraint(foodcap[itm, bp] <= limited.Maximum * fv,
$"cap for relative modifier for food {fd} in slot {bp}");
}
FoodExprs.AddExprToDict(bp, foodcap[itm, bp]);
}
}
}
}
private void CreateGearModel()
{
foreach (var grp in GearChoices.GroupBy(g => g.EquipSlotCategory))
{
// if gear is unique, equip it once only.
grp.Where(e => e.IsUnique)
.ForEach(
e =>
Model.AddConstraint(Expression.Sum(grp.Key.PossibleSlots.Select(s => gear[s, e])) <= 1,
$"ensure gear uniqueness for {e}"));
// SIMPLIFICATION: we ignore blocked slots
foreach (var s in grp.Key.PossibleSlots)
{
// choose at most one gear per slot
Model.AddConstraint(Expression.Sum(grp.Select(e => gear[s, e])) <= 1,
$"choose at most one item for slot {s}");
foreach (var e in grp)
{
var gv = gear[s, e];
// ASSUMPTION: all gear choices have fixed parameters
e.AllParameters.Where(p => RelevantStats.Contains(p.BaseParam))
.ForEach(
p =>
AddExprToDict(StatExprs, p.BaseParam,
p.Values.Sum(v => ((ParameterValueFixed)v).Amount) * gv));
// ASSUMPTION: all meldable items have at least one materia slot
// ASSUMPTION: customisable relics are unmeldable
if (e.FreeMateriaSlots > 0)
{
CreateMateriaModel(s, e);
}
else if (RelicCaps != null && RelicCaps.ContainsKey(e))
{
CreateRelicModel(s, e);
}
}
}
}
}
/// <summary>
/// Creates a new BiS solver model.
/// </summary>
/// <param name="solverConfig">Solver configuration</param>
/// <param name="job">Job to solve for</param>
/// <param name="gearChoices">Gear items to choose from. Keep this small.</param>
/// <param name="foodChoices">List of food choices. This can be fairly large, it doesn't add much complexity.</param>
/// <param name="materiaChoices">
/// Dictionary of materia choices; set value to true if the materia is allowed for advanced
/// melding. The materia with the highest eligible stat value is chosen. (Note that Tier is 0-indexed)
/// </param>
//TODO: this is getting out of hand. need config object asap.
//TODO: make model parts pluggable if possible
public BisModel(SolverConfig solverConfig, ClassJob job,
IEnumerable <Equipment> gearChoices, IEnumerable <FoodItem> foodChoices,
IDictionary <MateriaItem, bool> materiaChoices)
{
Model = new Model();
SolverConfig = solverConfig;
Job = job;
JobConfig = SolverConfig.JobConfigs[Job];
GearChoices = gearChoices.ToList();
FoodChoices = foodChoices.ToList();
// collect stats we care about
RelevantStats = JobConfig.Weights.Keys.Union(JobConfig.StatRequirements.Keys).ToList();
// we don't care about materia which affect unneeded stats
MateriaChoices = materiaChoices.Where(m => RelevantStats.Contains(m.Key.BaseParam))
.ToDictionary(k => k.Key, k => k.Value);
var allEquipSlots = GearChoices.SelectMany(g => g.EquipSlotCategory.PossibleSlots).ToList();
gear = new VariableCollection <EquipSlot, Equipment>(Model, allEquipSlots, GearChoices,
type: VariableType.Binary,
debugNameGenerator: (s, e) => new StringBuilder().AppendFormat("{0}_{1}", s, e),
lowerBoundGenerator: (s, e) => CheckRequired(e) ? 1 : 0);
food = new VariableCollection <FoodItem>(Model, FoodChoices,
type: VariableType.Binary,
debugNameGenerator: e => new StringBuilder().AppendFormat("{0}", e.Item),
lowerBoundGenerator: i => CheckRequired(i.Item) ? 1 : 0);
foodcap = new VariableCollection <FoodItem, BaseParam>(Model, FoodChoices, RelevantStats,
type: VariableType.Integer,
debugNameGenerator: (i, bp) => new StringBuilder().AppendFormat("{0}_{1}_cap", i.Item, bp),
lowerBoundGenerator: (x, b) => 0);
materia = new VariableCollection <EquipSlot, Equipment, MateriaItem>(Model, allEquipSlots, GearChoices, MateriaChoices.Keys,
type: VariableType.Integer,
debugNameGenerator: (s, e, m) => new StringBuilder().AppendFormat("{2}_{0}_{1}", s, e, m),
lowerBoundGenerator: (s, e, bp) => 0,
upperBoundGenerator: (s, e, b) => e.TotalMateriaSlots());
cap = new VariableCollection <EquipSlot, Equipment, BaseParam>(Model, allEquipSlots, GearChoices, RelevantStats,
type: VariableType.Integer,
debugNameGenerator: (s, e, bp) => new StringBuilder().AppendFormat("{2}_cap_{0}_{1}", s, e, bp),
lowerBoundGenerator: (s, e, b) => 0);
relicBase = new VariableCollection <EquipSlot, Equipment, BaseParam>(Model, allEquipSlots, GearChoices, RelevantStats,
type: VariableType.Integer,
debugNameGenerator: (s, e, bp) => new StringBuilder().AppendFormat("{2}_relic_base_{0}_{1}", s, e, bp),
lowerBoundGenerator: (s, e, b) => 0);
stat = new VariableCollection <BaseParam>(Model, RelevantStats,
type: VariableType.Integer,
debugNameGenerator: bp => new StringBuilder().AppendFormat("gear_materia__{0}", bp),
lowerBoundGenerator: x => 0);
modstat = new VariableCollection <BaseParam>(Model, RelevantStats,
type: VariableType.Integer,
debugNameGenerator: bp => new StringBuilder().AppendFormat("added_food_{0}", bp),
lowerBoundGenerator: x => 0);
allocstat = new VariableCollection <BaseParam>(Model, RelevantStats,
type: VariableType.Integer,
debugNameGenerator: bp => new StringBuilder().AppendFormat("allocated_{0}", bp),
lowerBoundGenerator: x => 0, upperBoundGenerator: x => SolverConfig.AllocatedStatsCap);
tieredstat = new VariableCollection <BaseParam>(Model, RelevantStats,
type: VariableType.Integer,
debugNameGenerator: bp => new StringBuilder().AppendFormat("tiered_{0}", bp),
lowerBoundGenerator: x => 0);
Model.AddConstraint(
Expression.Sum(RelevantStats.Where(bp => MainStats.Contains(bp.Name)).Select(bp => allocstat[bp])) <=
SolverConfig.AllocatedStatsCap,
"cap allocatable stats");
StatExprs = RelevantStats.ToDictionary(bp => bp, bp => Expression.EmptyExpression);
FoodExprs = RelevantStats.ToDictionary(bp => bp, bp => (Expression)stat[bp]);
SolverConfig.BaseStats.ForEach(kv => StatExprs[kv.Key] = kv.Value + Expression.EmptyExpression);
CreateGearModel();
CreateMateriaOrdering();
CreateFoodModel();
CreateTiers();
CreateObjective();
}
private void CreateGearModel()
{
foreach (var grp in GearChoices.GroupBy(g => g.EquipSlotCategory))
{
// if gear is unique, equip it once only.
if (grp.Key.PossibleSlots.Count() > 1)
{
grp.Where(e => e.IsUnique)
.ForEach(
e =>
Model.AddConstraint(Expression.Sum(grp.Key.PossibleSlots.Select(s => gear[s, e])) <= 1,
$"ensure gear uniqueness for {e}"));
}
// SIMPLIFICATION: we ignore blocked slots
foreach (var s in grp.Key.PossibleSlots)
{
// choose at most one gear per slot
Model.AddConstraint(Expression.Sum(grp.Select(e => gear[s, e])) <= 1,
$"choose at most one item for slot {s}");
foreach (var e in grp)
{
var gv = gear[s, e];
// ASSUMPTION: all gear choices have fixed parameters
var stats =
e.AllParameters.Where(p => RelevantStats.Contains(p.BaseParam))
.ToDictionary(p => p.BaseParam,
p => p.Values.OfType <ParameterValueFixed>().Select(val => val.Amount).Sum());
if (SolverConfig.EquipmentOverrides?.ContainsKey(e) ?? false)
{
var statsOverride = SolverConfig.EquipmentOverrides[e];
if (statsOverride == null)
{
continue;
}
foreach (var kv in statsOverride)
{
stats[kv.Key] = kv.Value;
}
}
// sanity check stats
foreach (var kv in stats)
{
if (e.GetMaximumParamValue(kv.Key) < kv.Value)
{
Console.Error.WriteLine($"{kv.Key} => {kv.Value} for {e} is out of range");
}
}
stats.ForEach(p => StatExprs.AddExprToDict(p.Key, p.Value * gv));
// ASSUMPTION: all meldable items have at least one materia slot
// ASSUMPTION: customisable relics are unmeldable
if (e.FreeMateriaSlots > 0)
{
CreateMateriaModel(s, e);
}
else
{
CreateRelicModel(s, e);
}
}
}
}
}
/// <summary>
/// Creates a new BiS solver model.
/// </summary>
/// <param name="weights">Stat weights. The higher the weight, the more a stat is desirable</param>
/// <param name="statReqs">Minimum amount of stats that must be present in a solution</param>
/// <param name="baseStats">Stats of a character without any gear</param>
/// <param name="gearChoices">Gear items to choose from. Keep this small.</param>
/// <param name="foodChoices">List of food choices. This can be fairly large, it doesn't add much complexity.</param>
/// <param name="materiaChoices">
/// Dictionary of materia choices; set value to true if the materia is allowed for advanced
/// melding. The materia with the highest eligible stat value is chosen. (Note that Tier is 0-indexed)
/// </param>
/// <param name="relicCaps">Designates customizable relics. Value of an entry determines the total stat cap.</param>
/// <param name="overmeldThreshold">
/// Extend the overmelding threshold --- i.e. if you set overmeldThreshold to n, materia
/// from materiaChoices that isn't normally allowed in advanced melds can be used up to n times in advanced meld
/// </param>
/// <param name="allocStatCap">Cap for allocatable stats. Default is 35</param>
/// <param name="maximizeUnweightedValues">Maximize unweighted values with a small weight (1e-5)</param>
//TODO: this is getting out of hand. need config object asap.
//TODO: make model parts pluggable if possible
public BisModel(IDictionary <BaseParam, double> weights, IDictionary <BaseParam, int> statReqs,
IDictionary <BaseParam, int> baseStats, IEnumerable <Equipment> gearChoices, IEnumerable <FoodItem> foodChoices,
IDictionary <MateriaItem, bool> materiaChoices, IDictionary <Equipment, int> relicCaps = null,
int overmeldThreshold = 0, int allocStatCap = 35, bool maximizeUnweightedValues = true)
{
Model = new Model();
StatRequirements = statReqs;
Weights = weights;
GearChoices = gearChoices.ToList();
FoodChoices = foodChoices.ToList();
RelicCaps = relicCaps;
OvermeldThreshold = overmeldThreshold;
MaximizeUnweightedValues = maximizeUnweightedValues;
// collect stats we care about
RelevantStats = Weights.Keys.Union(StatRequirements.Keys).ToList();
// we don't care about materia which affect unneeded stats
MateriaChoices = materiaChoices.Where(m => RelevantStats.Contains(m.Key.BaseParam))
.ToDictionary(k => k.Key, k => k.Value);
var allEquipSlots = GearChoices.SelectMany(g => g.EquipSlotCategory.PossibleSlots).ToList();
gear = new VariableCollection <EquipSlot, Equipment>(Model, allEquipSlots, GearChoices,
type: VariableType.Binary);
food = new VariableCollection <FoodItem>(Model, FoodChoices, type: VariableType.Binary);
foodcap = new VariableCollection <FoodItem, BaseParam>(Model, FoodChoices, RelevantStats,
type: VariableType.Integer,
lowerBoundGenerator: (x, b) => 0);
materia = new VariableCollection <EquipSlot, Equipment, MateriaItem>(Model, allEquipSlots, GearChoices,
MateriaChoices.Keys,
type: VariableType.Integer, lowerBoundGenerator: (s, e, bp) => 0);
cap = new VariableCollection <EquipSlot, Equipment, BaseParam>(Model, allEquipSlots, GearChoices,
RelevantStats, type: VariableType.Integer, lowerBoundGenerator: (s, e, b) => 0);
stat = new VariableCollection <BaseParam>(Model, RelevantStats, type: VariableType.Integer,
lowerBoundGenerator: x => 0);
modstat = new VariableCollection <BaseParam>(Model, RelevantStats, type: VariableType.Integer,
lowerBoundGenerator: x => 0);
allocstat = new VariableCollection <BaseParam>(Model, RelevantStats, type: VariableType.Integer,
lowerBoundGenerator: x => 0);
Model.AddConstraint(
Expression.Sum(RelevantStats.Where(bp => MainStats.Contains(bp.Name)).Select(bp => allocstat[bp])) <=
allocStatCap,
"cap allocatable stats");
StatExprs = RelevantStats.ToDictionary(bp => bp, bp => Expression.EmptyExpression);
FoodExprs = RelevantStats.ToDictionary(bp => bp, bp => (Expression)stat[bp]);
baseStats.ForEach(kv => StatExprs[kv.Key] = kv.Value + Expression.EmptyExpression);
var bigM = 50 *
GearChoices.Select(
g =>
g.AllParameters.Select(
p => p.Values.OfType <ParameterValueFixed>().Select(v => v.Amount).Max())
.Max()).Max();
CreateGearModel();
CreateFoodModel();
CreateObjective();
}