diff --git a/optimierung_pymoo.ipynb b/optimierung_pymoo.ipynb index 823c93744a112020eb4fa818177a6f480be23fbf..d25b51e705b3bdde3e21e94fe83b20400db1e1d4 100644 --- a/optimierung_pymoo.ipynb +++ b/optimierung_pymoo.ipynb @@ -111,13 +111,6 @@ "execution_count": 3, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[('source', 12.0), ('pump1', 12.0), ('pump2', 8.0), ('valveA', 4.0), ('valveB', 4.0), ('valveC', 4.0)]\n" - ] - }, { "data": { "image/png": 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", @@ -166,8 +159,7 @@ " for outF in graph.successors(node):\n", " if SC!=0. and not'valve' in outF:\n", " graph[node][outF][0]['weight']=tempF/SC\n", - " else:continue\n", - "print(graph.nodes.data('flow'))" + " else:continue" ] }, { @@ -214,12 +206,13 @@ "Spalten = kanten\n", "Summe pro knoten = 0\n", "\n", - "Q pump muss größer gleich sein als alle nachfolgenden durchflüsse" + ".Q_valve <= .Q\n", + ".Q['pumps']==.Q**2['successors']" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -259,15 +252,25 @@ " ),LR_P.coef_\n", " ) for i in modell.pumps)\n", "modell.Power_Objective = pyo.Objective(rule=PumpPower,sense=pyo.minimize)\n", + "\n", + "#expressions for constraints:\n", "def PumpFlow(modell,pump):\n", " return np.dot(np.array([modell.Q[pump]**2,modell.n[pump]*modell.Q[pump],modell.n[pump]**2]),LR_H.coef_)\n", - "def Flow_req(modell,p):\n", - " return PumpFlow(modell,p) - pyo.summation(modell.Q,index=graph.successors(p))\n", - "modell.Flow_Objective = pyo.Objective(modell.pumps,rule=Flow_req,sense=pyo.minimize)\n", + "def Pump_delivery_req(modell,pump):\n", + " return PumpFlow(modell,pump) + (pyo.summation(modell.Q,index=graph.successors(pump))**2)==0.\n", + "\n", + "\n", + "def valve_req_rule(modell,valve):\n", + " return pyo.summation(modell.Q,index=graph.predecessors(valve))>=modell.Q_valve[valve]\n", + "\n", + "#modell.Flow_Objective = pyo.Objective(modell.pumps,rule=Flow_req,sense=pyo.minimize)\n", "\n", "#Constaints\n", "def continuityRule(modell,node):\n", " return pyo.summation(modell.Q, index=graph.predecessors(node))==pyo.summation(modell.Q, index=graph.successors(node))\n", + "\n", + "\n", + "\n", "#alternative\n", "def continuityRule2(modell,node):\n", " return 0.==sum(graph[node][i][0]['weight'] for i in graph[node])\n", @@ -282,13 +285,7 @@ " 'Q_valve':{'valveA':4.,'valveB':4.,'valveC':4.},\n", " }\n", "}\n", - "print(TestData)\n", - "#data=DataPortal(data_dict=TestData)\n", - "\n", - "#Optimierungsgleichung\n", - "#modell.pump_constraint = pyo.Constraint(expr=sum(modell.nodes[k] for k in modell.nodes)==0,rule=continuityRule)\n", - "#instance=modell.create_instance(graph,LR_H)\n", - "#instance.obj = pyo.Objective(expr=sum(PumpPower(modell.Q[i],modell.n[i],LR_P) for i in modell.pumps),sense=min)\n" + "print(TestData)" ] }, { @@ -304,16 +301,88 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SCIP version 9.2.0 [precision: 8 byte] [memory: block] [mode: optimized] [LP solver: Soplex 7.1.2] [GitHash: 74cea9222e]\n", + "Copyright (c) 2002-2024 Zuse Institute Berlin (ZIB)\n", + "\n", + "External libraries: \n", + " Soplex 7.1.2 Linear Programming Solver developed at Zuse Institute Berlin (soplex.zib.de) [GitHash: b040369c]\n", + " CppAD 20180000.0 Algorithmic Differentiation of C++ algorithms developed by B. Bell (github.com/coin-or/CppAD)\n", + " TinyCThread 1.2 small portable implementation of the C11 threads API (tinycthread.github.io)\n", + " MPIR 3.0.0 Multiple Precision Integers and Rationals Library developed by W. Hart (mpir.org)\n", + " ZIMPL 3.6.2 Zuse Institute Mathematical Programming Language developed by T. Koch (zimpl.zib.de)\n", + " AMPL/MP 690e9e7 AMPL .nl file reader library (github.com/ampl/mp)\n", + " PaPILO 2.4.0 parallel presolve for integer and linear optimization (github.com/scipopt/papilo) (built with TBB) [GitHash: 2d9fe29f]\n", + " Nauty 2.8.8 Computing Graph Automorphism Groups by Brendan D. McKay (users.cecs.anu.edu.au/~bdm/nauty)\n", + " sassy 1.1 Symmetry preprocessor by Markus Anders (github.com/markusa4/sassy)\n", + " Ipopt 3.14.16 Interior Point Optimizer developed by A. Waechter et.al. (github.com/coin-or/Ipopt)\n", + "\n", + "user parameter file <scip.set> not found - using default parameters\n", + "read problem <C:\\Users\\STEINM~1\\AppData\\Local\\Temp\\tmpn32p48nz.pyomo.nl>\n", + "============\n", + "\n", + "original problem has 9 variables (0 bin, 0 int, 0 impl, 9 cont) and 12 constraints\n", + "\n", + "solve problem\n", + "=============\n", + "\n", + "presolving:\n", + "(round 1, fast) 2 del vars, 6 del conss, 0 add conss, 5 chg bounds, 0 chg sides, 0 chg coeffs, 0 upgd conss, 0 impls, 0 clqs\n", + "presolving (2 rounds: 2 fast, 0 medium, 0 exhaustive):\n", + " 2 deleted vars, 6 deleted constraints, 0 added constraints, 5 tightened bounds, 0 added holes, 0 changed sides, 0 changed coefficients\n", + " 0 implications, 0 cliques\n", + "presolving detected infeasibility\n", + "Presolving Time: 0.00\n", + "\n", + "SCIP Status : problem is solved [infeasible]\n", + "Solving Time (sec) : 0.00\n", + "Solving Nodes : 0\n", + "Primal Bound : +1.00000000000000e+20 (0 solutions)\n", + "Dual Bound : +1.00000000000000e+20\n", + "Gap : 0.00 %\n", + "WARNING: Loading a SolverResults object with a warning status into\n", + "model.name=\"unknown\";\n", + " - termination condition: infeasible\n", + " - message from solver: infeasible\n", + "\n", + "Problem: \n", + "- Lower bound: -inf\n", + " Upper bound: inf\n", + " Number of objectives: 1\n", + " Number of constraints: 0\n", + " Number of variables: 0\n", + " Sense: unknown\n", + "Solver: \n", + "- Status: warning\n", + " Message: infeasible\n", + " Termination condition: infeasible\n", + " Id: 200\n", + " Error rc: 0\n", + " Time: 0.047808170318603516\n", + "Solution: \n", + "- number of solutions: 0\n", + " number of solutions displayed: 0\n", + "\n" + ] + } + ], "source": [ "from pyomo.opt import SolverFactory\n", "\n", - "#opt = pyo.SolverFactory('scipampl', executable=r'C:\\Program Files\\SCIPOptSuite 9.2.0\\bin\\scip.exe')\n", + "opt = pyo.SolverFactory('scipampl', executable=r'C:\\Program Files\\SCIPOptSuite 9.2.0\\bin\\scip.exe')\n", "instance = modell.create_instance(TestData)\n", "instance.Continuity_constaint=pyo.Constraint(instance.nodes, rule=continuityRule)\n", - "#result=opt.solve(instance, tee=True)\n" + "instance.Flow_constraint=pyo.Constraint(instance.valves,rule=valve_req_rule)\n", + "instance.pump_Flow_constraint=pyo.Constraint(instance.pumps,rule=Pump_delivery_req)\n", + "result=opt.solve(instance, tee=True)\n", + "\n", + "print(result)" ] } ],