{"version":3,"file":"index.node.cjs","sources":["index.node.js"],"sourcesContent":["import { readFileSync } from 'fs';\n\n/** Loads a fresh HiGHS WebAssembly module with the given options. */\nasync function loadHiGHSModule(options) {\n const createModule = await loadHiGHSFactory();\n const consoleConfig = options?.console ?? { log: null, error: null };\n const moduleOptions = {\n print: consoleConfig.log ?? (() => { }),\n printErr: consoleConfig.error ?? (() => { }),\n };\n return createModule(moduleOptions);\n}\nasync function loadHiGHSFactory() {\n const { default: HiGHSModuleFactory } = await import(new URL('../build/highs.js', import.meta.url).href);\n return HiGHSModuleFactory;\n}\n\nconst HIGHS_STATUS_MAP = {\n 0: 'unknown', // kNotset\n 1: 'error', // kLoadError\n 2: 'error', // kModelError\n 3: 'error', // kPresolveError\n 4: 'error', // kSolveError\n 5: 'error', // kPostsolveError\n 6: 'error', // kModelEmpty\n 7: 'optimal', // kOptimal\n 8: 'infeasible', // kInfeasible\n 9: 'unboundedorinfeasible', // kUnboundedOrInfeasible\n 10: 'unbounded', // kUnbounded\n 11: 'objectivebound', // kObjectiveBound\n 12: 'objectivetarget', // kObjectiveTarget\n 13: 'timelimit', // kTimeLimit\n 14: 'iterationlimit', // kIterationLimit\n 15: 'unknown', // kUnknown\n 16: 'solutionlimit', // kSolutionLimit\n 17: 'unknown', // kInterrupt\n 18: 'unknown', // kMemoryLimit\n 19: 'unknown', // kHighsInterrupt\n};\n/** Low-level wrapper around the HiGHS optimization solver. */\nlet HiGHS$1 = class HiGHS {\n constructor(module, highsPtr) {\n this.freed = false;\n this.module = module;\n this.highsPtr = highsPtr;\n }\n /** Creates a new HiGHS solver instance. */\n static async create(options) {\n const module = await loadHiGHSModule(options);\n const highsPtr = module.ccall('Highs_create', 'number', [], []);\n if (highsPtr === 0) {\n throw new Error('Highs_create failed to create instance');\n }\n return new HiGHS(module, highsPtr);\n }\n /** Parses a problem from a string in the given format (e.g., 'lp', 'mps'). */\n async parse(content, format) {\n this.ensureNotFreed();\n const filename = `/tmp/problem.${format}`;\n this.module.FS.writeFile(filename, content);\n try {\n const status = this.module.ccall('Highs_readModel', 'number', ['number', 'string'], [this.highsPtr, filename]);\n if (status !== 0) {\n throw new Error(`Highs_readModel failed with status ${status}`);\n }\n }\n finally {\n try {\n this.module.FS.unlink(filename);\n }\n catch {\n // Ignore cleanup errors\n }\n }\n }\n /** Sets a HiGHS option by name. Supports boolean, integer, real, and string values. */\n setParam(name, value) {\n this.ensureNotFreed();\n if (typeof value === 'boolean') {\n this.module.ccall('Highs_setBoolOptionValue', 'number', ['number', 'string', 'number'], [this.highsPtr, name, value ? 1 : 0]);\n }\n else if (typeof value === 'string') {\n this.module.ccall('Highs_setStringOptionValue', 'number', ['number', 'string', 'string'], [this.highsPtr, name, value]);\n }\n else if (Number.isInteger(value)) {\n this.module.ccall('Highs_setIntOptionValue', 'number', ['number', 'string', 'number'], [this.highsPtr, name, value]);\n }\n else {\n this.module.ccall('Highs_setDoubleOptionValue', 'number', ['number', 'string', 'number'], [this.highsPtr, name, value]);\n }\n }\n /** Solves the loaded problem and returns the result. */\n async solve() {\n this.ensureNotFreed();\n this.module.ccall('Highs_run', 'number', ['number'], [this.highsPtr]);\n const statusCode = this.module.ccall('Highs_getModelStatus', 'number', ['number'], [this.highsPtr]);\n const status = HIGHS_STATUS_MAP[statusCode] ?? 'unknown';\n const result = { status };\n if (status === 'optimal' || status === 'timelimit' ||\n status === 'solutionlimit' || status === 'objectivebound' ||\n status === 'objectivetarget') {\n result.objective = this.module.ccall('Highs_getObjectiveValue', 'number', ['number'], [this.highsPtr]);\n result.solution = this.extractSolution();\n }\n return result;\n }\n extractSolution() {\n const solution = new Map();\n const numCol = this.module.ccall('Highs_getNumCol', 'number', ['number'], [this.highsPtr]);\n const colValuePtr = this.module._malloc(numCol * 8);\n try {\n this.module.ccall('Highs_getSolution', 'number', ['number', 'number', 'number', 'number', 'number'], [this.highsPtr, colValuePtr, 0, 0, 0]);\n const nameBufferSize = 256;\n const namePtr = this.module._malloc(nameBufferSize);\n try {\n for (let i = 0; i < numCol; i++) {\n this.module.ccall('Highs_getColName', 'number', ['number', 'number', 'number'], [this.highsPtr, i, namePtr]);\n const name = this.module.UTF8ToString(namePtr);\n const value = this.module.getValue(colValuePtr + i * 8, 'double');\n solution.set(name, value);\n }\n }\n finally {\n this.module._free(namePtr);\n }\n }\n finally {\n this.module._free(colValuePtr);\n }\n return solution;\n }\n /** Frees the HiGHS instance. Safe to call multiple times. */\n free() {\n if (this.freed) {\n return;\n }\n this.freed = true;\n this.module.ccall('Highs_destroy', null, ['number'], [this.highsPtr]);\n }\n ensureNotFreed() {\n if (this.freed) {\n throw new Error('HiGHS instance has been freed');\n }\n }\n};\n\n/** A linear constraint: expr sense rhs (e.g., x + y <= 10). */\nclass Constraint {\n /** @internal Use leq(), geq(), or eq() methods on expressions instead. */\n constructor(expr, sense, rhs, name) {\n this.expr = expr;\n this.sense = sense;\n this.rhs = rhs;\n this.name = name;\n }\n}\n\n/** A linear expression: sum of terms plus a constant. */\nclass LinExpr {\n /** @internal Use variable arithmetic methods (plus, minus, times) instead. */\n constructor(terms, constant) {\n this.terms = terms;\n this.constant = constant;\n }\n /** Returns this + other. */\n plus(other) {\n if (typeof other === 'number') {\n return new LinExpr(this.terms, this.constant + other);\n }\n if (other instanceof LinExpr) {\n return new LinExpr([...this.terms, ...other.terms], this.constant + other.constant);\n }\n return new LinExpr([...this.terms, { coeff: 1, var: other }], this.constant);\n }\n /** Returns this - other. */\n minus(other) {\n if (typeof other === 'number') {\n return new LinExpr(this.terms, this.constant - other);\n }\n if (other instanceof LinExpr) {\n const negatedTerms = other.terms.map((t) => ({ coeff: -t.coeff, var: t.var }));\n return new LinExpr([...this.terms, ...negatedTerms], this.constant - other.constant);\n }\n return new LinExpr([...this.terms, { coeff: -1, var: other }], this.constant);\n }\n /** Returns coeff * this. */\n times(coeff) {\n return new LinExpr(this.terms.map((t) => ({ coeff: t.coeff * coeff, var: t.var })), this.constant * coeff);\n }\n /** Returns -this. */\n neg() {\n return this.times(-1);\n }\n /** Returns a constraint: this <= rhs. */\n leq(rhs) {\n return new Constraint(this, '<=', rhs);\n }\n /** Returns a constraint: this >= rhs. */\n geq(rhs) {\n return new Constraint(this, '>=', rhs);\n }\n /** Returns a constraint: this == rhs. */\n eq(rhs) {\n return new Constraint(this, '=', rhs);\n }\n}\n\n/** A decision variable in an optimization model. */\nclass Var {\n /** @internal Use Model.numVar(), Model.intVar(), or Model.boolVar() instead. */\n constructor(name, type, lb, ub) {\n this.name = name;\n this.type = type;\n this.lb = lb;\n this.ub = ub;\n }\n toExpr() {\n return new LinExpr([{ coeff: 1, var: this }], 0);\n }\n /** Returns this + other. */\n plus(other) {\n return this.toExpr().plus(other);\n }\n /** Returns this - other. */\n minus(other) {\n return this.toExpr().minus(other);\n }\n /** Returns coeff * this. */\n times(coeff) {\n return new LinExpr([{ coeff, var: this }], 0);\n }\n /** Returns -this. */\n neg() {\n return this.times(-1);\n }\n /** Returns a constraint: this <= rhs. */\n leq(rhs) {\n return this.toExpr().leq(rhs);\n }\n /** Returns a constraint: this >= rhs. */\n geq(rhs) {\n return this.toExpr().geq(rhs);\n }\n /** Returns a constraint: this == rhs. */\n eq(rhs) {\n return this.toExpr().eq(rhs);\n }\n}\n\n/** The result of solving a Model. */\nclass Solution {\n /** @internal Use Model.solve() to obtain a Solution. */\n constructor(result) {\n this.status = result.status;\n this.objective = result.objective;\n this.values = result.solution ?? new Map();\n }\n /** Returns the value of a variable in the solution, or undefined if not found. */\n getValue(variable) {\n return this.values.get(variable.name);\n }\n}\n\nfunction toLPFormat(input) {\n const lines = [];\n if (input.sense === 'maximize') {\n lines.push('Maximize');\n }\n else {\n lines.push('Minimize');\n }\n if (input.objective) {\n lines.push(` obj: ${formatExpr(input.objective)}`);\n }\n else {\n lines.push(' obj: 0');\n }\n lines.push('Subject To');\n let constraintIndex = 0;\n for (const constraint of input.constraints) {\n const name = constraint.name ?? `c${constraintIndex++}`;\n const exprStr = formatExpr(constraint.expr);\n const senseStr = constraint.sense === '=' ? '=' : constraint.sense;\n const rhs = constraint.rhs - constraint.expr.constant;\n lines.push(` ${name}: ${exprStr} ${senseStr} ${formatNumber(rhs)}`);\n }\n const boundsLines = [];\n const generalVars = [];\n const binaryVars = [];\n for (const v of input.variables) {\n if (v.type === 'binary') {\n binaryVars.push(v.name);\n }\n else {\n if (v.type === 'integer') {\n generalVars.push(v.name);\n }\n const hasNonDefaultBounds = v.lb !== 0 || v.ub !== Infinity;\n if (hasNonDefaultBounds) {\n if (v.ub === Infinity) {\n boundsLines.push(` ${formatNumber(v.lb)} <= ${v.name}`);\n }\n else {\n boundsLines.push(` ${formatNumber(v.lb)} <= ${v.name} <= ${formatNumber(v.ub)}`);\n }\n }\n }\n }\n if (boundsLines.length > 0) {\n lines.push('Bounds');\n lines.push(...boundsLines);\n }\n if (generalVars.length > 0) {\n lines.push('General');\n lines.push(` ${generalVars.join(' ')}`);\n }\n if (binaryVars.length > 0) {\n lines.push('Binary');\n lines.push(` ${binaryVars.join(' ')}`);\n }\n lines.push('End');\n return lines.join('\\n') + '\\n';\n}\nfunction formatExpr(expr) {\n const consolidated = consolidateTerms(expr);\n if (consolidated.length === 0) {\n return '0';\n }\n const parts = [];\n for (let i = 0; i < consolidated.length; i++) {\n const { coeff, varName } = consolidated[i];\n if (coeff === 0)\n continue;\n if (i === 0) {\n if (coeff === 1) {\n parts.push(varName);\n }\n else if (coeff === -1) {\n parts.push(`- ${varName}`);\n }\n else if (coeff < 0) {\n parts.push(`- ${formatNumber(-coeff)} ${varName}`);\n }\n else {\n parts.push(`${formatNumber(coeff)} ${varName}`);\n }\n }\n else {\n if (coeff === 1) {\n parts.push(`+ ${varName}`);\n }\n else if (coeff === -1) {\n parts.push(`- ${varName}`);\n }\n else if (coeff < 0) {\n parts.push(`- ${formatNumber(-coeff)} ${varName}`);\n }\n else {\n parts.push(`+ ${formatNumber(coeff)} ${varName}`);\n }\n }\n }\n return parts.join(' ') || '0';\n}\nfunction consolidateTerms(expr) {\n const coeffMap = new Map();\n for (const term of expr.terms) {\n const current = coeffMap.get(term.var.name) ?? 0;\n coeffMap.set(term.var.name, current + term.coeff);\n }\n const result = [];\n for (const [varName, coeff] of coeffMap) {\n if (coeff !== 0) {\n result.push({ coeff, varName });\n }\n }\n return result;\n}\nfunction formatNumber(n) {\n if (Number.isInteger(n)) {\n return n.toString();\n }\n return n.toString();\n}\n\n/**\n * Converts a model to fixed MPS format. Uses the modern \"free\" MPS format\n * which doesn't require strict column alignment.\n */\nfunction toMPSFormat(input) {\n const lines = [];\n const constraintNames = [];\n lines.push('NAME problem');\n if (input.sense === 'maximize') {\n lines.push('OBJSENSE');\n lines.push(' MAX');\n }\n // ROWS section: objective and constraints\n lines.push('ROWS');\n lines.push(' N obj');\n let constraintIndex = 0;\n for (const constraint of input.constraints) {\n const name = constraint.name ?? `c${constraintIndex++}`;\n constraintNames.push(name);\n const rowType = constraint.sense === '<=' ? 'L' : constraint.sense === '>=' ? 'G' : 'E';\n lines.push(` ${rowType} ${name}`);\n }\n // COLUMNS section: variable coefficients\n lines.push('COLUMNS');\n // Build coefficient map: varName -> { rowName -> coeff }\n const varCoeffs = new Map();\n for (const v of input.variables) {\n varCoeffs.set(v.name, new Map());\n }\n // Add objective coefficients\n if (input.objective) {\n for (const term of input.objective.terms) {\n const coeffs = varCoeffs.get(term.var.name);\n const current = coeffs.get('obj') ?? 0;\n coeffs.set('obj', current + term.coeff);\n }\n }\n // Add constraint coefficients\n for (let i = 0; i < input.constraints.length; i++) {\n const constraint = input.constraints[i];\n const rowName = constraintNames[i];\n for (const term of constraint.expr.terms) {\n const coeffs = varCoeffs.get(term.var.name);\n const current = coeffs.get(rowName) ?? 0;\n coeffs.set(rowName, current + term.coeff);\n }\n }\n // Output columns, marking integer variables\n const integerVars = input.variables.filter(v => v.type === 'integer' || v.type === 'binary');\n const continuousVars = input.variables.filter(v => v.type === 'continuous');\n for (const v of continuousVars) {\n const coeffs = varCoeffs.get(v.name);\n for (const [rowName, coeff] of coeffs) {\n if (coeff !== 0) {\n lines.push(` ${v.name} ${rowName} ${coeff}`);\n }\n }\n }\n if (integerVars.length > 0) {\n lines.push(\" MARKER 'MARKER' 'INTORG'\");\n for (const v of integerVars) {\n const coeffs = varCoeffs.get(v.name);\n for (const [rowName, coeff] of coeffs) {\n if (coeff !== 0) {\n lines.push(` ${v.name} ${rowName} ${coeff}`);\n }\n }\n }\n lines.push(\" MARKER 'MARKER' 'INTEND'\");\n }\n // RHS section\n lines.push('RHS');\n for (let i = 0; i < input.constraints.length; i++) {\n const constraint = input.constraints[i];\n const rowName = constraintNames[i];\n const rhs = constraint.rhs - constraint.expr.constant;\n if (rhs !== 0) {\n lines.push(` rhs ${rowName} ${rhs}`);\n }\n }\n // BOUNDS section\n const hasBounds = input.variables.some(v => v.type !== 'binary' && (v.lb !== 0 || v.ub !== Infinity));\n const hasBinary = input.variables.some(v => v.type === 'binary');\n if (hasBounds || hasBinary) {\n lines.push('BOUNDS');\n for (const v of input.variables) {\n if (v.type === 'binary') {\n lines.push(` BV bnd ${v.name}`);\n }\n else {\n if (v.lb !== 0) {\n lines.push(` LO bnd ${v.name} ${v.lb}`);\n }\n if (v.ub !== Infinity) {\n lines.push(` UP bnd ${v.name} ${v.ub}`);\n }\n else if (v.lb === 0) {\n lines.push(` PL bnd ${v.name}`);\n }\n }\n }\n }\n lines.push('ENDATA');\n return lines.join('\\n') + '\\n';\n}\n\n/** Computes tight lower and upper bounds on a linear expression from variable bounds. */\nfunction exprBounds(expr) {\n if (expr instanceof Var) {\n return { lb: expr.lb, ub: expr.ub };\n }\n let lb = expr.constant;\n let ub = expr.constant;\n for (const term of expr.terms) {\n if (term.coeff > 0) {\n lb += term.coeff * term.var.lb;\n ub += term.coeff * term.var.ub;\n }\n else {\n lb += term.coeff * term.var.ub;\n ub += term.coeff * term.var.lb;\n }\n }\n return { lb, ub };\n}\n/** Returns true if the expression is guaranteed to take integer values. */\nfunction isIntegral(expr) {\n if (expr instanceof Var) {\n return expr.type === 'integer' || expr.type === 'binary';\n }\n if (!Number.isInteger(expr.constant))\n return false;\n for (const term of expr.terms) {\n const varIsInt = term.var.type === 'integer' || term.var.type === 'binary';\n if (!varIsInt || !Number.isInteger(term.coeff))\n return false;\n }\n return true;\n}\n/** @internal Validates that a variable is binary, throwing if not. */\nfunction assertBinary(v, context) {\n const isBinary = v.type === 'binary' ||\n (v.type === 'integer' && v.lb === 0 && v.ub === 1);\n if (!isBinary) {\n throw new Error(`${context}: variable '${v.name}' must be binary`);\n }\n}\n\n/** Returns the sum of the given variables, expressions, and constants. */\nfunction sum(...items) {\n let result = new LinExpr([], 0);\n for (const item of items) {\n result = result.plus(item);\n }\n return result;\n}\n\nfunction isBinary(v) {\n return v.type === 'binary' || (v.type === 'integer' && v.lb === 0 && v.ub === 1);\n}\n/** High-level model builder for optimization problems. */\nclass Model {\n constructor() {\n this.variables = [];\n this.constraints = [];\n this.objective = null;\n this.sense = 'minimize';\n this.varCounter = 0;\n }\n /** Creates a continuous variable with the given bounds and optional name. */\n numVar(lb = 0, ub = Infinity, name) {\n const varName = name ?? `x${this.varCounter++}`;\n const v = new Var(varName, 'continuous', lb, ub);\n this.variables.push(v);\n return v;\n }\n /** Creates an integer variable with the given bounds and optional name. */\n intVar(lb = 0, ub = Infinity, name) {\n const varName = name ?? `x${this.varCounter++}`;\n const v = new Var(varName, 'integer', lb, ub);\n this.variables.push(v);\n return v;\n }\n /** Creates a binary (0-1) variable with an optional name. */\n boolVar(name) {\n const varName = name ?? `x${this.varCounter++}`;\n const v = new Var(varName, 'binary', 0, 1);\n this.variables.push(v);\n return v;\n }\n /** Adds a constraint to the model with an optional name. */\n addConstraint(constraint, name) {\n if (name !== undefined)\n constraint.name = name;\n this.constraints.push(constraint);\n }\n /** Sets the objective to minimize the given expression. */\n minimize(expr) {\n this.objective = expr instanceof Var ? expr.times(1) : expr;\n this.sense = 'minimize';\n }\n /** Sets the objective to maximize the given expression. */\n maximize(expr) {\n this.objective = expr instanceof Var ? expr.times(1) : expr;\n this.sense = 'maximize';\n }\n /** Returns a variable equal to the logical AND of the given binary variables. */\n and(...vars) {\n if (vars.length === 0)\n throw new Error('and() requires at least 1 variable');\n if (vars.length === 1)\n return vars[0];\n for (const v of vars)\n assertBinary(v, 'and()');\n const z = this.boolVar();\n for (const v of vars)\n this.addConstraint(z.minus(v).leq(0));\n this.addConstraint(sum(z, ...vars.map((v) => v.neg())).geq(1 - vars.length));\n return z;\n }\n /** Returns a variable equal to the logical OR of the given binary variables. */\n or(...vars) {\n if (vars.length === 0)\n throw new Error('or() requires at least 1 variable');\n if (vars.length === 1)\n return vars[0];\n for (const v of vars)\n assertBinary(v, 'or()');\n const z = this.boolVar();\n for (const v of vars)\n this.addConstraint(z.minus(v).geq(0));\n this.addConstraint(sum(...vars).minus(z).geq(0));\n return z;\n }\n /** Returns a variable equal to the logical NOT of a binary variable. */\n not(x) {\n assertBinary(x, 'not()');\n const z = this.boolVar();\n this.addConstraint(z.plus(x).eq(1));\n return z;\n }\n /** Returns a variable equal to the XOR of two binary variables. */\n xor(x, y, options) {\n assertBinary(x, 'xor()');\n assertBinary(y, 'xor()');\n const z = this.boolVar();\n if (options?.method === 'compact') {\n const w = this.and(x, y);\n this.addConstraint(z.minus(x).minus(y).plus(w.times(2)).eq(0));\n }\n else {\n this.addConstraint(z.minus(x).minus(y).leq(0));\n this.addConstraint(z.minus(x).plus(y).geq(0));\n this.addConstraint(z.plus(x).minus(y).geq(0));\n this.addConstraint(z.plus(x).plus(y).leq(2));\n }\n return z;\n }\n /** Adds an implication constraint: x=1 implies y=1. */\n addImplication(x, y) {\n assertBinary(x, 'addImplication()');\n assertBinary(y, 'addImplication()');\n this.addConstraint(x.minus(y).leq(0));\n }\n /** Adds a cardinality constraint: at most k of the given variables are 1. */\n addAtMost(k, ...vars) {\n for (const v of vars)\n assertBinary(v, 'addAtMost()');\n this.addConstraint(sum(...vars).leq(k));\n }\n /** Adds a cardinality constraint: at least k of the given variables are 1. */\n addAtLeast(k, ...vars) {\n for (const v of vars)\n assertBinary(v, 'addAtLeast()');\n this.addConstraint(sum(...vars).geq(k));\n }\n /** Adds a cardinality constraint: exactly k of the given variables are 1. */\n addExactly(k, ...vars) {\n for (const v of vars)\n assertBinary(v, 'addExactly()');\n this.addConstraint(sum(...vars).eq(k));\n }\n /**\n * Adds an indicator constraint: when delta equals the active value, the\n * given constraint is enforced via Big-M relaxation.\n */\n addIndicator(delta, constraint, options) {\n assertBinary(delta, 'addIndicator()');\n const active = options?.active ?? 1;\n const { expr, sense, rhs } = constraint;\n if (sense === '<=' || sense === '=') {\n const M = options?.bigM ?? this.computeBigM(expr, rhs, '<=', 'addIndicator()');\n if (active === 1) {\n this.addConstraint(expr.plus(delta.times(M)).leq(rhs + M));\n }\n else {\n this.addConstraint(expr.minus(delta.times(M)).leq(rhs));\n }\n }\n if (sense === '>=' || sense === '=') {\n const M = options?.bigM ?? this.computeBigM(expr, rhs, '>=', 'addIndicator()');\n if (active === 1) {\n this.addConstraint(expr.minus(delta.times(M)).geq(rhs - M));\n }\n else {\n this.addConstraint(expr.plus(delta.times(M)).geq(rhs));\n }\n }\n }\n /**\n * Returns a variable equal to the absolute value of the given expression,\n * using sign decomposition with a boolean selector variable.\n */\n abs(expr, options) {\n const e = expr instanceof Var ? expr.times(1) : expr;\n const { lb: L, ub: U } = options?.bigM != null\n ? { lb: -options.bigM, ub: options.bigM }\n : this.finiteBounds(e, 'abs()');\n const posMax = Math.max(U, 0);\n const negMax = Math.max(-L, 0);\n const xPlus = this.numVar(0, posMax);\n const xMinus = this.numVar(0, negMax);\n const delta = this.boolVar();\n const t = this.numVar(0, Math.max(posMax, negMax));\n this.addConstraint(e.minus(xPlus).plus(xMinus).eq(0));\n this.addConstraint(xPlus.plus(xMinus).minus(t).eq(0));\n this.addConstraint(xPlus.minus(delta.times(posMax)).leq(0));\n this.addConstraint(xMinus.plus(delta.times(negMax)).leq(negMax));\n return t;\n }\n /**\n * Returns a variable equal to the maximum of the given expressions, using\n * Big-M with boolean selectors.\n */\n max(exprs, options) {\n if (exprs.length === 0)\n throw new Error('max() requires at least 1 expression');\n if (exprs.length === 1) {\n const e = exprs[0];\n if (e instanceof Var)\n return e;\n const t = this.numVar(-Infinity, Infinity);\n this.addConstraint(e.minus(t).eq(0));\n return t;\n }\n const es = exprs.map((e) => (e instanceof Var ? e.times(1) : e));\n const bounds = es.map((e) => options?.bigM != null\n ? { lb: -options.bigM, ub: options.bigM }\n : this.finiteBounds(e, 'max()'));\n const maxUb = Math.max(...bounds.map((b) => b.ub));\n const minLb = Math.min(...bounds.map((b) => b.lb));\n const deltas = es.map(() => this.boolVar());\n const t = this.numVar(minLb, maxUb);\n for (let i = 0; i < es.length; i++) {\n const Mi = maxUb - bounds[i].lb;\n this.addConstraint(t.minus(es[i]).geq(0));\n this.addConstraint(t.minus(es[i]).plus(deltas[i].times(Mi)).leq(Mi));\n }\n this.addConstraint(sum(...deltas).eq(1));\n return t;\n }\n /**\n * Returns a variable equal to the minimum of the given expressions, using\n * Big-M with boolean selectors.\n */\n min(exprs, options) {\n if (exprs.length === 0)\n throw new Error('min() requires at least 1 expression');\n if (exprs.length === 1) {\n const e = exprs[0];\n if (e instanceof Var)\n return e;\n const t = this.numVar(-Infinity, Infinity);\n this.addConstraint(e.minus(t).eq(0));\n return t;\n }\n const es = exprs.map((e) => (e instanceof Var ? e.times(1) : e));\n const bounds = es.map((e) => options?.bigM != null\n ? { lb: -options.bigM, ub: options.bigM }\n : this.finiteBounds(e, 'min()'));\n const maxUb = Math.max(...bounds.map((b) => b.ub));\n const minLb = Math.min(...bounds.map((b) => b.lb));\n const t = this.numVar(minLb, maxUb);\n const deltas = es.map(() => this.boolVar());\n for (let i = 0; i < es.length; i++) {\n const Mi = bounds[i].ub - minLb;\n this.addConstraint(t.minus(es[i]).leq(0));\n this.addConstraint(t.minus(es[i]).minus(deltas[i].times(Mi)).geq(-Mi));\n }\n this.addConstraint(sum(...deltas).eq(1));\n return t;\n }\n /**\n * Returns a variable equal to the product of two variables. 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[x, y] : [y, x];\n const { lb: L, ub: U } = options?.bigM != null\n ? { lb: -options.bigM, ub: options.bigM }\n : this.finiteBounds(z, 'product()');\n const w = this.numVar(Math.min(L, 0), Math.max(U, 0));\n this.addConstraint(w.minus(delta.times(U)).leq(0));\n this.addConstraint(w.minus(delta.times(L)).geq(0));\n this.addConstraint(w.minus(z).minus(delta.times(L)).leq(-L));\n this.addConstraint(w.minus(z).minus(delta.times(U)).geq(-U));\n return w;\n }\n /**\n * Creates a semi-continuous variable that is either 0 or in [lb, ub].\n * Requires 0 < lb <= ub.\n */\n semiContVar(lb, ub, name) {\n if (lb <= 0 || ub < lb) {\n throw new Error('semiContVar(): requires 0 < lb <= ub');\n }\n const x = this.numVar(0, ub, name);\n const delta = this.boolVar();\n this.addConstraint(x.minus(delta.times(lb)).geq(0));\n this.addConstraint(x.minus(delta.times(ub)).leq(0));\n return x;\n }\n /**\n * Returns quotient and remainder variables for integer division of expr by d.\n * Requires expr >= 0 with finite upper bound, and d a positive integer.\n */\n divMod(expr, d) {\n if (!Number.isInteger(d) || d <= 0) {\n throw new Error('divMod(): d must be a positive integer');\n }\n const e = expr instanceof Var ? expr.times(1) : expr;\n const { lb, ub } = this.finiteBounds(e, 'divMod()');\n if (lb < 0) {\n throw new Error('divMod(): expression must be non-negative');\n }\n const q = this.intVar(0, Math.floor(ub / d));\n const r = this.intVar(0, d - 1);\n this.addConstraint(e.minus(q.times(d)).minus(r).eq(0));\n return { quotient: q, remainder: r };\n }\n /** Enforces that at least one of the two constraints holds. */\n addEitherOr(c1, c2, options) {\n const delta = this.boolVar();\n this.addIndicator(delta, c1, { active: 0, bigM: options?.bigM });\n this.addIndicator(delta, c2, { active: 1, bigM: options?.bigM });\n }\n /**\n * Returns a binary variable delta where delta=1 iff the constraint is satisfied.\n * Supports <=, >=, and = senses.\n */\n reify(constraint, options) {\n const { expr, sense, rhs } = constraint;\n if (sense === '<=') {\n return this.reifyLeqInternal(expr, rhs, options);\n }\n if (sense === '>=') {\n return this.reifyLeqInternal(expr.neg(), -rhs, options);\n }\n return this.reifyEqInternal(expr, rhs, options);\n }\n reifyLeqInternal(expr, rhs, options) {\n const { lb, ub } = options?.bigM != null\n ? { lb: -options.bigM + rhs, ub: options.bigM + rhs }\n : this.finiteBounds(expr, 'reify()');\n const M = ub - rhs;\n const m = lb - rhs;\n const eps = options?.epsilon ?? this.defaultEpsilon(expr, rhs);\n const delta = this.boolVar();\n this.addConstraint(expr.plus(delta.times(M)).leq(rhs + M));\n this.addConstraint(expr.minus(delta.times(m - eps)).geq(rhs + eps));\n return delta;\n }\n reifyEqInternal(expr, rhs, options) {\n const { lb, ub } = options?.bigM != null\n ? { lb: -options.bigM + rhs, ub: options.bigM + rhs }\n : this.finiteBounds(expr, 'reify()');\n const Mpos = ub - rhs;\n const Mneg = rhs - lb;\n const M = Math.max(Mpos, Mneg);\n const eps = options?.epsilon ?? this.defaultEpsilon(expr, rhs);\n const delta = this.boolVar();\n const mu = this.boolVar();\n this.addConstraint(expr.plus(delta.times(M)).leq(rhs + M));\n this.addConstraint(expr.minus(delta.times(M)).geq(rhs - M));\n this.addConstraint(expr.plus(delta.times(M + eps)).plus(mu.times(M + eps)).geq(rhs + eps));\n this.addConstraint(expr.minus(delta.times(M + eps)).plus(mu.times(M + eps)).leq(rhs - eps + (M + eps)));\n return delta;\n }\n defaultEpsilon(expr, rhs) {\n return isIntegral(expr) && Number.isInteger(rhs) ? 1 : 1e-6;\n }\n computeBigM(expr, rhs, sense, context) {\n const { lb, ub } = this.finiteBounds(expr, context);\n return sense === '<=' ? ub - rhs : rhs - lb;\n }\n finiteBounds(expr, context) {\n const b = exprBounds(expr);\n if (!isFinite(b.lb) || !isFinite(b.ub)) {\n throw new Error(`${context}: cannot auto-compute Big-M because expression has infinite bounds. ` +\n 'Either bound all variables or provide an explicit { bigM } option.');\n }\n return b;\n }\n /** Prints the model in the specified format (defaults to LP). */\n print(format = 'lp') {\n const input = {\n objective: this.objective,\n sense: this.sense,\n constraints: this.constraints,\n variables: this.variables,\n };\n return format === 'mps' ? toMPSFormat(input) : toLPFormat(input);\n }\n /** Solves the model and returns the solution. */\n async solve(options) {\n const lpString = this.print();\n const highs = await HiGHS$1.create(options);\n try {\n await highs.parse(lpString, 'lp');\n const result = await highs.solve();\n return new Solution(result);\n }\n finally {\n highs.free();\n }\n }\n}\n\n/** HiGHS solver with Node.js-specific file reading support. */\nclass HiGHS extends HiGHS$1 {\n /** Reads a problem from a file path. The format is inferred from the extension. */\n async readProblem(path) {\n const content = readFileSync(path, 'utf-8');\n const ext = path.split('.').pop() || 'lp';\n await this.parse(content, ext);\n }\n static async create(options) {\n const base = await HiGHS$1.create(options);\n return Object.setPrototypeOf(base, HiGHS.prototype);\n }\n}\n\nexport { Constraint, HiGHS, LinExpr, Model, Solution, Var, exprBounds, isIntegral, sum };\n//# 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