second_order_conic_programming_0010.ipynb

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      "minimizer: [-1.707790, -2.044676, -0.852738, -2.544822, -2.485651] , fx = -1.7077904490804823\n"
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    "/**\n",
    " * Demonstrate how to solve a Second-Order Conic Programming (SOCP) problem using interior point method.\n",
    " *\n",
    " * @author Haksun Li\n",
    " */\n",
    "\n",
    "%use s2\n",
    "import dev.nm.solver.IterativeSolution\n",
    "\n",
    "// construct an SOCP problem to solve\n",
    "fun problem() : SOCPGeneralProblem {\n",
    "    // min f'x\n",
    "    val f: Vector = DenseVector(1.0, 0.0, 0.0, 0.0, 0.0)\n",
    "\n",
    "    // The A's in the conic constraints.\n",
    "    val A1t: Matrix = DenseMatrix(arrayOf(doubleArrayOf(0.0, -1.0, 0.0, 1.0, 0.0), doubleArrayOf(0.0, 0.0, 1.0, 0.0, -1.0)))\n",
    "    val A2t: Matrix = DenseMatrix(arrayOf(doubleArrayOf(0.0, 0.5, 0.0, 0.0, 0.0), doubleArrayOf(0.0, 0.0, 1.0, 0.0, 0.0)))\n",
    "    val A3t: Matrix = DenseMatrix(arrayOf(doubleArrayOf(0.0, 0.0, 0.0, -0.7071, -0.7071), doubleArrayOf(0.0, 0.0, 0.0, -0.3536, 0.3536)))\n",
    "\n",
    "    // The b's in the conic constraints.\n",
    "    val b1: Vector = f\n",
    "    val b2: Vector = f.ZERO()\n",
    "    val b3: Vector = f.ZERO()\n",
    "\n",
    "    // The c's in the conic constraints.\n",
    "    val c1: Vector = DenseVector(2) // zero\n",
    "    val c2: Vector = DenseVector(-0.5, 0.0)\n",
    "    val c3: Vector = DenseVector(4.2426, -0.7071)\n",
    "\n",
    "    // The d's in the conic constraints.\n",
    "    val d = doubleArrayOf(0.0, 1.0, 1.0)\n",
    "    val constraints: kotlin.collections.List<SOCPGeneralConstraint> = java.util.Arrays.asList<SOCPGeneralConstraint>(\n",
    "        SOCPGeneralConstraint(A1t.t(), c1, b1, d[0]),\n",
    "        SOCPGeneralConstraint(A2t.t(), c2, b2, d[1]),\n",
    "        SOCPGeneralConstraint(A3t.t(), c3, b3, d[2])\n",
    "    )\n",
    "\n",
    "    // The SOCP problem to be solved.\n",
    "    val problem: SOCPGeneralProblem = SOCPGeneralProblem(\n",
    "        f, \n",
    "        constraints) // ||Ax + b|| <= c'x + d\n",
    "    return problem\n",
    "}\n",
    "\n",
    "// Uses interior point method to solve the given problem from a given starting point.\n",
    "val x0: Vector = DenseVector(1.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.1, 0.0, 0.0)\n",
    "val s0: Vector = DenseVector(3.7, 1.0, -3.5, 1.0, 0.25, 0.5, 1.0, -0.35355, -0.1767)\n",
    "val y0: Vector = DenseVector(-3.7, -1.5, -0.5, -2.5, -4.0)\n",
    "// an initial guess\n",
    "val soln0 = PrimalDualSolution(x0, s0, y0)\n",
    "\n",
    "// construct an SOCP solver\n",
    "val solver = PrimalDualInteriorPointMinimizer(\n",
    "    1e-8,\n",
    "    20) // max number of iterations\n",
    "\n",
    "// solve the SOCP problem\n",
    "val p = problem()\n",
    "val soln: IterativeSolution<PrimalDualSolution> = solver.solve(p)\n",
    "soln.search(soln0)\n",
    "\n",
    "// the solution\n",
    "val y = soln.minimizer().y\n",
    "val fx = p.f().evaluate(y);\n",
    "println(\"minimizer: $y, fx = $fx\")"
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