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| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 0 |
39B |
| 1 |
411.25KB |
| 1.1 Material.pdf |
893.54KB |
| 1.1 ortools_ex.py |
1.19KB |
| 1. Congratulation.mp4 |
1.40MB |
| 1. Congratulation.srt |
775B |
| 1. CP Ortools.mp4 |
50.76MB |
| 1. CP Ortools.srt |
4.57KB |
| 1. Installing Python.mp4 |
13.90MB |
| 1. Installing Python.srt |
3.05KB |
| 1. Introduction.mp4 |
13.48MB |
| 1. Introduction.mp4 |
1.01MB |
| 1. Introduction.srt |
3.52KB |
| 1. Introduction.srt |
816B |
| 1. Lists, Tuples, and Dictionary.mp4 |
49.19MB |
| 1. Lists, Tuples, and Dictionary.srt |
9.28KB |
| 1. LP Introduction.mp4 |
6.26MB |
| 1. LP Introduction.srt |
3.37KB |
| 1. MILP Introduction.mp4 |
5.73MB |
| 1. MILP Introduction.srt |
2.23KB |
| 1. MINLP Introduction.mp4 |
2.56MB |
| 1. MINLP Introduction.srt |
1.20KB |
| 1. NLP Introduction.mp4 |
2.78MB |
| 1. NLP Introduction.srt |
1.32KB |
| 1. Pyomo Using other solvers (CBC).mp4 |
36.31MB |
| 1. Pyomo Using other solvers (CBC).srt |
3.68KB |
| 10 |
247.97KB |
| 11 |
401.54KB |
| 12 |
318.20KB |
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283.23KB |
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123.95KB |
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| 16 |
498.20KB |
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426.57KB |
| 18 |
193.32KB |
| 19 |
263.83KB |
| 2 |
94.64KB |
| 2.1 ex_area.py |
562B |
| 2.1 inputs.xlsx |
9.40KB |
| 2.1 Ipopt-3.11.1-win64-intel13.1.zip |
9.89MB |
| 2.1 Material.pdf |
893.54KB |
| 2.1 pyomo_ex.py |
721B |
| 2.1 pyomo_ex.py |
672B |
| 2.2 pyomo_array_sum.py |
947B |
| 2.2 pyomo_ex.py |
698B |
| 2. Framework and Solvers.mp4 |
6.00MB |
| 2. Framework and Solvers.srt |
2.51KB |
| 2. Garden problem.mp4 |
37.99MB |
| 2. Garden problem.srt |
4.37KB |
| 2. If, For, While.mp4 |
54.71MB |
| 2. If, For, While.srt |
10.77KB |
| 2. MILP Pyomo.mp4 |
22.60MB |
| 2. MILP Pyomo.srt |
3.74KB |
| 2. MINLP Pyomo (Couenne).mp4 |
23.84MB |
| 2. MINLP Pyomo (Couenne).srt |
3.21KB |
| 2. NLP Pyomo (IPOPT).mp4 |
25.79MB |
| 2. NLP Pyomo (IPOPT).srt |
3.00KB |
| 2. Packages.mp4 |
3.47MB |
| 2. Packages.srt |
1.45KB |
| 2. Pyomo Summations.mp4 |
198.18MB |
| 2. Pyomo Summations.srt |
26.78KB |
| 2. What is optimization.mp4 |
23.25MB |
| 2. What is optimization.srt |
5.96KB |
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358.72KB |
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507.42KB |
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213.40KB |
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164.94KB |
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454.91KB |
| 26 |
30.19KB |
| 27 |
258.56KB |
| 28 |
412.37KB |
| 29 |
14.56KB |
| 3 |
423.77KB |
| 3.1 code.py |
106B |
| 3.1 ortools_ex.py |
405B |
| 3.1 ortools_ex.py |
406B |
| 3.1 pyomo_mindtpy_ex.py |
718B |
| 3.1 rotas_input.xlsx |
9.50KB |
| 3.1 scip_ex.py |
366B |
| 3.2 ex_rota.py |
1.49KB |
| 3.2 myFile.py |
99B |
| 3. Functions.mp4 |
24.98MB |
| 3. Functions.srt |
4.82KB |
| 3. IDE Spyder.mp4 |
13.80MB |
| 3. IDE Spyder.srt |
2.56KB |
| 3. LP Ortools.mp4 |
36.24MB |
| 3. LP Ortools.srt |
7.65KB |
| 3. MILP Ortools.mp4 |
7.27MB |
| 3. MILP Ortools.srt |
1.69KB |
| 3. MINLP Pyomo (decomposition using mindtpy).mp4 |
19.14MB |
| 3. MINLP Pyomo (decomposition using mindtpy).srt |
2.81KB |
| 3. NLP SCIP.mp4 |
11.63MB |
| 3. NLP SCIP.srt |
1.91KB |
| 3. Pyomo Pprint.mp4 |
19.54MB |
| 3. Pyomo Pprint.srt |
2.35KB |
| 3. Route problem.mp4 |
148.38MB |
| 3. Route problem.srt |
15.00KB |
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466.78KB |
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370.61KB |
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101.74KB |
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201.67KB |
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20.71KB |
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378.00KB |
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299.63KB |
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109.90KB |
| 38 |
232.39KB |
| 39 |
214.71KB |
| 4 |
130.92KB |
| 4.1 code.py |
184B |
| 4.1 ex_receita.py |
582B |
| 4.1 Pyomo - Optimization Modeling in Python (2017, Springer).pdf |
1.76MB |
| 4.1 scip_ex.py |
340B |
| 4.1 scip_ex.py |
335B |
| 4.1 scip_ex.py |
385B |
| 4.2 pyomo_manual3.pdf |
1.57MB |
| 4.3 pyomo_manual.pdf |
253.96KB |
| 4.4 pyomo_manual2.pdf |
10.21MB |
| 4. Jupyter NotebookLab.mp4 |
9.27MB |
| 4. Jupyter NotebookLab.srt |
2.88KB |
| 4. LP SCIP.mp4 |
44.38MB |
| 4. LP SCIP.srt |
6.53KB |
| 4. MILP SCIP.mp4 |
8.79MB |
| 4. MILP SCIP.srt |
1.92KB |
| 4. MINLP SCIP.mp4 |
7.75MB |
| 4. MINLP SCIP.srt |
1.26KB |
| 4. NLP Exercise, solve it by yourself.mp4 |
94.87MB |
| 4. Numpy.mp4 |
34.65MB |
| 4. Numpy.srt |
7.41KB |
| 4. Pyomo Manual.html |
59B |
| 4. Revenue problem.mp4 |
51.51MB |
| 4. Revenue problem.srt |
3.52KB |
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255.81KB |
| 41 |
300.41KB |
| 42 |
237.33KB |
| 43 |
245.03KB |
| 44 |
1.38KB |
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279.99KB |
| 46 |
26.63KB |
| 47 |
221.57KB |
| 48 |
452.73KB |
| 49 |
247.42KB |
| 5 |
267.33KB |
| 5.1 alg_gen.py |
878B |
| 5.1 code.py |
339B |
| 5.1 ex_opflinear.py |
1.90KB |
| 5.1 exercise_cos.py |
511B |
| 5. Exercises.html |
169B |
| 5. LP Gurobi, CPLEX, and GLPK.mp4 |
77.24MB |
| 5. LP Gurobi, CPLEX, and GLPK.srt |
10.79KB |
| 5. MILP Exercise, solve it by yourself.mp4 |
143.91MB |
| 5. MINLP Genetic Algorithm.mp4 |
37.01MB |
| 5. MINLP Genetic Algorithm.srt |
6.51KB |
| 5. NLP Exercise Solution.mp4 |
31.50MB |
| 5. NLP Exercise Solution.srt |
4.77KB |
| 5. Optimal power flow problem.mp4 |
127.59MB |
| 5. Optimal power flow problem.srt |
10.13KB |
| 5. Pandas.mp4 |
36.58MB |
| 5. Pandas.srt |
9.87KB |
| 50 |
439.14KB |
| 51 |
98.58KB |
| 52 |
505.42KB |
| 53 |
130.46KB |
| 6 |
150.30KB |
| 6.1 data.xlsx |
10.61KB |
| 6.1 exercise.py |
964B |
| 6.1 psopy_ex.py |
437B |
| 6.1 pyomo_ex.py |
653B |
| 6.2 pandas_excel.py |
334B |
| 6.3 output.xlsx |
4.89KB |
| 6. LP Pyomo.mp4 |
50.11MB |
| 6. LP Pyomo.srt |
8.28KB |
| 6. MILP Exercise solution.mp4 |
64.84MB |
| 6. MILP Exercise solution.srt |
8.26KB |
| 6. MINLP Particle Swarm (PSO).mp4 |
23.47MB |
| 6. MINLP Particle Swarm (PSO).srt |
3.55KB |
| 6. Pandas reading Excel.mp4 |
45.72MB |
| 6. Pandas reading Excel.srt |
7.98KB |
| 7 |
159.10KB |
| 7.1 code.py |
136B |
| 7.1 pulp_ex.py |
318B |
| 7. Graphs.mp4 |
19.99MB |
| 7. Graphs.srt |
4.03KB |
| 7. LP PuLP.mp4 |
23.56MB |
| 7. LP PuLP.srt |
4.85KB |
| 8 |
301.67KB |
| 8. Exercises.html |
169B |
| 8. Which solver and frameworks should we choose.mp4 |
7.71MB |
| 8. Which solver and frameworks should we choose.srt |
2.23KB |
| 9 |
505.36KB |
| 9.1 exercise.py |
742B |
| 9. LP Exercise, solve it by yourself.mp4 |
70.35MB |
| TutsNode.com.txt |
63B |