Optimization with Python Solve Operations Research Problems
Torrent Info
| Category | Other |
| Added | Tuesday 24th October 2023 05:15:59 PM (3 years ago) |
| Size | 3.0 GB |
| Peers | 2 Peers (1 Seeders and 1 leechers) update |
| Downloaded | 640 times |
| Uploader | tutsnode Thank You (0) Report Torrent 00/0 |
| Comments | None |
| Uploader Comments | None |
| Tags | English |
| Seeders | 1 |
| Leechers | 1 |
Torrent Screenshots
NFO
No NFO was added for this torrent.
| Filename | Size |
|---|---|
| 001 Introduction and a new Case Study (hands-on).mp4 | 249.8 MB |
| TutsNode.com.txt | 63 bytes |
| 35532022-CBC-manual-and-parameters.pdf | 188.6 KB |
| 002 Check the solver progress_en.srt | 5.1 KB |
| 002 CP_ Concepts.html | 88 bytes |
| 0 | 1 byte |
| 002 Pyomo_ Summations.mp4 | 198.2 MB |
| 33907028-0-Mathematical-Programming.pdf | 799.6 KB |
| 002 Pyomo_ Summations_en.srt | 26.8 KB |
| 001 Installing Python_en.srt | 2.9 KB |
| 002 Garden problem_en.srt | 8.8 KB |
| 002 Packages_en.srt | 1.4 KB |
| 36020664-TSP-Simple-Literature-Review.pdf | 557.1 KB |
| 003 IDE Spyder_en.srt | 2.5 KB |
| 36020652-JobShopSchedulling-Article.pdf | 359.5 KB |
| 004 Jupyter Notebook_Lab_en.srt | 2.8 KB |
| 001 Introduction and a new Case Study (hands-on)_en.srt | 25.5 KB |
| 009 Example 4_ route problem_en.srt | 21.5 KB |
| 010 Rules with indexes_en.srt | 16.5 KB |
| 002 SCOP_ Second-Order Cone Programming_en.srt | 15.2 KB |
| 004 Route problem [subtitled]_en.srt | 15.0 KB |
| 001 Congratulation_en.srt | 6.8 KB |
| 33101356-ex-MINLP-scip.py | 385 bytes |
| 1 | 1 byte |
| 009 Example 4_ route problem.mp4 | 166.3 MB |
| 33907054-2-Duality-Theory.pdf | 544.4 KB |
| 005 Linearization_ binary_continuos using BigM_en.srt | 14.9 KB |
| 007 Example 2_ investiment_en.srt | 14.3 KB |
| 008 Example 3_ production cost_en.srt | 13.5 KB |
| 003 Define a Gap Limit_en.srt | 11.3 KB |
| 008 PDFs to learn more about Python.html | 322 bytes |
| 32779002-sist-eletrico.xlsx | 10.8 KB |
| 005 LP_ Gurobi, CPLEX, and GLPK (installation)_en.srt | 10.8 KB |
| 32608798-myFile.py | 99 bytes |
| 33101168-ex-function.py | 106 bytes |
| 33101174-ex-numpy.py | 184 bytes |
| 33101176-ex-pandas.py | 339 bytes |
| 33101190-ex-pandas-excel.py | 334 bytes |
| 33101198-ex-graphs.py | 136 bytes |
| 002 If, For, While_en.srt | 10.8 KB |
| 32608776-data.xlsx | 10.6 KB |
| 001 CP_ Ortools_en.srt | 10.2 KB |
| 005 Optimal power flow problem [subtitled]_en.srt | 10.1 KB |
| 012 Example 7_ job assignment_en.srt | 10.1 KB |
| 002 How do we solve optimization problems__en.srt | 2.7 KB |
| 005 Pandas_en.srt | 9.9 KB |
| 32608890-rotas-input.xlsx | 9.5 KB |
| 32608856-inputs.xlsx | 9.4 KB |
| 004 Objective Function and Constraints_en.srt | 1.6 KB |
| 010 Example 5_ construction assignment_en.srt | 8.4 KB |
| 005 How to model your problem__en.srt | 2.0 KB |
| 35532010-glpk.pdf | 467.0 KB |
| 36020666-VRPTW.pdf | 356.0 KB |
| 008 Parameters and Sets_en.srt | 9.1 KB |
| 001 Lists, Tuples, and Dictionary_en.srt | 8.9 KB |
| 006 Example 1_ investiment_en.srt | 8.8 KB |
| 006 LP_ Pyomo (using Gurobi, CPLEX, and GLPK)_en.srt | 8.3 KB |
| 006 MILP_ Exercise solution_en.srt | 8.3 KB |
| 003 LP_ Ortools_en.srt | 7.7 KB |
| 006 Pandas_ reading Excel_en.srt | 8.0 KB |
| 003 Revenue problem_en.srt | 7.5 KB |
| 004 Numpy_en.srt | 7.4 KB |
| 003 Type of Variables_en.srt | 7.4 KB |
| 004 LP_ SCIP_en.srt | 6.5 KB |
| 005 MINLP_ Genetic Algorithm_en.srt | 6.5 KB |
| 003 NonConvex Quadratic Programming_en.srt | 6.4 KB |
| 013 Example 8_ job assignment_en.srt | 1.7 KB |
| 006 Linearization_ binary_binary_en.srt | 6.3 KB |
| 002 What is optimization_en.srt | 5.7 KB |
| 015 Some references for you learn more (problems of VRPTW, TSP, JobShop...).html | 1.5 KB |
| 36020614-ex1-investiment.py | 861 bytes |
| 36020622-ex2-investiment.py | 983 bytes |
| 36020624-ex3-cost-of-production.py | 810 bytes |
| 36020632-ex3-cost-of-production-with-binary.py | 995 bytes |
| 36020638-ex5-construction.py | 658 bytes |
| 36020640-ex6-construction-binary.py | 814 bytes |
| 36020644-ex7-jobs.py | 1.0 KB |
| 36020650-ex8-jobs-with-limit.py | 1.1 KB |
| 004 Define a Time Limit_en.srt | 5.6 KB |
| 011 Example 6_ construction assignment_en.srt | 5.0 KB |
| 32608778-output.xlsx | 4.9 KB |
| 007 LP_ PuLP_en.srt | 4.9 KB |
| 003 Functions_en.srt | 4.8 KB |
| 36020670-ex4-route.py | 1.7 KB |
| 005 NLP_ Exercise Solution_en.srt | 4.8 KB |
| 012 Differential Algebraic Equations (DAE)_en.srt | 4.6 KB |
| 009 Rules inside Constraints_en.srt | 4.3 KB |
| 002 Framework and Solvers_en.srt | 2.5 KB |
| 007 Graphs_en.srt | 4.0 KB |
| 004 Vehicle Routing Problems (VRP) with Or-Tools, An introduction_en.srt | 4.0 KB |
| 002 MILP_ Pyomo_en.srt | 3.7 KB |
| 001 Pyomo_ Using other solvers (CBC)_en.srt | 3.7 KB |
| 006 Working with inequality_en.srt | 3.6 KB |
| 007 MINLP_ Particle Swarm (PSO)_en.srt | 3.6 KB |
| 001 Introduction_en.srt | 3.4 KB |
| 014 How to Learn More__en.srt | 3.4 KB |
| 001 LP_ Introduction_en.srt | 3.4 KB |
| 33101342-ex-NLP-scip.py | 366 bytes |
| 2 | 23 bytes |
| 005 MILP_ Exercise, solve it by yourself.mp4 | 143.9 MB |
| 001 What is Mathematical Modelling__en.srt | 3.3 KB |
| 010 LP_ Concepts.html | 245 bytes |
| 33101210-ex-LP-ortools.py | 405 bytes |
| 33101214-ex-LP-scip.py | 340 bytes |
| 33101230-ex-LP-pyomo.py | 653 bytes |
| 33101240-ex-LP-pulp.py | 318 bytes |
| 33101252-ex-LP-exercise.py | 742 bytes |
| 002 MINLP_ Pyomo (Couenne)_en.srt | 3.2 KB |
| 005 More parameters for the solvers.html | 3.1 KB |
| 002 NLP_ Pyomo (IPOPT)_en.srt | 3.0 KB |
| 001 Introduction_en.srt | 2.9 KB |
| 003 MINLP_ Pyomo (decomposition using mindtpy)_en.srt | 2.8 KB |
| 007 pyo.summation_en.srt | 2.6 KB |
| 011 WarmStart_en.srt | 2.5 KB |
| 003 Pyomo_ Pprint_en.srt | 2.3 KB |
| 008 Which solver and frameworks should we choose__en.srt | 2.2 KB |
| 001 MILP_ Introduction_en.srt | 2.2 KB |
| 004 Pyomo_ Manual.html | 59 bytes |
| 004 MILP_ SCIP_en.srt | 1.9 KB |
| 33101274-ex-pyomo-array-sum.py | 947 bytes |
| 003 NLP_ SCIP_en.srt | 1.9 KB |
| 33101368-examples-opflinear.py | 1.9 KB |
| 001 Introduction_en.srt | 1.9 KB |
| 003 MILP_ Ortools_en.srt | 1.7 KB |
| 33912172-features-rules.py | 1.5 KB |
| 33101376-examples-route.py | 1.5 KB |
| 34172722-Special-BinBin-GLPK.py | 1.3 KB |
| 001 NLP_ Introduction_en.srt | 1.3 KB |
| 33911722-features-param-sets.py | 1.3 KB |
| 33912170-features-rules-before.py | 1.3 KB |
| 004 MINLP_ SCIP_en.srt | 1.3 KB |
| 33782382-Special-BinCont-BIGM.py | 1.2 KB |
| 001 MINLP_ Introduction_en.srt | 1.2 KB |
| 33101364-ex-CP-ortools.py | 1.2 KB |
| 007 MILP_ Concepts.html | 121 bytes |
| 33101318-ex-MILP-pyomo.py | 672 bytes |
| 33101326-ex-MILP-ortools.py | 406 bytes |
| 33101328-ex-MILP-scip.py | 335 bytes |
| 33101334-ex-MILP-exercise.py | 964 bytes |
| 34172728-Special-BinBin-Gurobi.py | 1.2 KB |
| 33911694-features-TimeLimit.py | 1.2 KB |
| 33911678-features-GAP.py | 1.1 KB |
| 33911698-features-inequality.py | 1.1 KB |
| 33911704-features-summation-before.py | 1.1 KB |
| 33911648-features-solverProgress.py | 1.1 KB |
| 33911672-features-GAP-before.py | 1.1 KB |
| 33911708-features-summation.py | 1.1 KB |
| 33911716-features-param-sets-before.py | 1.1 KB |
| 33911592-features-casestudy.py | 1.1 KB |
| 33911640-features-solverProgress-before.py | 1.1 KB |
| 33782388-Special-BinCont-Gurobi.py | 1.0 KB |
| 006 NLP_ Concepts.html | 68 bytes |
| 33782374-Special-NCQP.py | 999 bytes |
| 33101338-ex-NLP-pyomo.py | 698 bytes |
| 33782370-Special-SOCP.py | 964 bytes |
| 33101344-ex-NLP-exercise-cos.py | 511 bytes |
| 33782372-original-problem.py | 964 bytes |
| 33782378-original-problem.py | 964 bytes |
| 33782528-original-problem.py | 964 bytes |
| 33101360-ex-GA.py | 878 bytes |
| 33101350-ex-MINLP-pyomo.py | 721 bytes |
| 33101352-ex-MINLP-pyomo-mindtpy.py | 718 bytes |
| [TGx]Downloaded from torrentgalaxy.to .txt | 585 bytes |
| 33101372-examples-receita.py | 582 bytes |
| 32608888-ex-area.py | 562 bytes |
| 33101366-examples-area.py | 562 bytes |
| 33101362-ex-PSO.py | 437 bytes |
| 006 MINLP_ Genetic Algorithm Concepts.html | 271 bytes |
| 008 MINLP_ PSO Concepts.html | 248 bytes |
| 3 | 11.3 KB |
| 002 SCOP_ Second-Order Cone Programming.mp4 | 136.5 MB |
| 33912962-python-basics.pdf | 325.7 KB |
| 4 | 205.9 KB |
| 005 Linearization_ binary_continuos using BigM.mp4 | 123.5 MB |
| 33913006-Constraint-Programming.pdf | 300.1 KB |
| 5 | 249.0 KB |
| 012 Example 7_ job assignment.mp4 | 107.9 MB |
| 6 | 77.9 KB |
| 004 NLP_ Exercise, solve it by yourself.mp4 | 94.9 MB |
| 7 | 130.9 KB |
| 002 Garden problem.mp4 | 92.8 MB |
| 8 | 231.0 KB |
| 006 Linearization_ binary_binary.mp4 | 92.0 MB |
| 9 | 25.6 KB |
| 005 Optimal power flow problem [subtitled].mp4 | 91.6 MB |
| 36020660-TSP-Book-Chapter.pdf | 263.2 KB |
| 10 | 139.0 KB |
| 010 Rules with indexes.mp4 | 74.4 MB |
| 11 | 608.0 KB |
| 004 Route problem [subtitled].mp4 | 72.1 MB |
| 12 | 906.6 KB |
| 009 LP_ Exercise, solve it by yourself.mp4 | 70.4 MB |
| 13 | 662.3 KB |
| 005 LP_ Gurobi, CPLEX, and GLPK (installation).mp4 | 59.4 MB |
| 14 | 624.3 KB |
| 003 Revenue problem.mp4 | 58.7 MB |
| 15 | 293.4 KB |
| 003 Define a Gap Limit.mp4 | 58.2 MB |
| 16 | 774.4 KB |
| 002 If, For, While.mp4 | 54.7 MB |
| 17 | 301.7 KB |
| 006 MILP_ Exercise solution.mp4 | 51.5 MB |
| 18 | 496.7 KB |
| 006 LP_ Pyomo (using Gurobi, CPLEX, and GLPK).mp4 | 50.1 MB |
| 19 | 913.5 KB |
| 007 Example 2_ investiment.mp4 | 40.9 MB |
| 20 | 92.3 KB |
| 008 Parameters and Sets.mp4 | 35.8 MB |
| 21 | 190.1 KB |
| 001 CP_ Ortools.mp4 | 35.0 MB |
| 22 | 8.2 KB |
| 005 NLP_ Exercise Solution.mp4 | 31.5 MB |
| 23 | 507.4 KB |
| 008 Example 3_ production cost.mp4 | 30.7 MB |
| 24 | 263.8 KB |
| 010 Example 5_ construction assignment.mp4 | 30.5 MB |
| 25 | 500.6 KB |
| 012 Differential Algebraic Equations (DAE).mp4 | 29.3 MB |
| 26 | 715.6 KB |
| 001 Pyomo_ Using other solvers (CBC).mp4 | 27.5 MB |
| 27 | 511.1 KB |
| 006 Pandas_ reading Excel.mp4 | 26.2 MB |
| 28 | 806.6 KB |
| 004 LP_ SCIP.mp4 | 26.1 MB |
| 29 | 957.0 KB |
| 003 LP_ Ortools.mp4 | 23.9 MB |
| 30 | 81.3 KB |
| 002 What is optimization.mp4 | 23.2 MB |
| 31 | 770.6 KB |
| 004 Vehicle Routing Problems (VRP) with Or-Tools, An introduction.mp4 | 22.0 MB |
| 32 | 15.7 KB |
| 001 Lists, Tuples, and Dictionary.mp4 | 21.1 MB |
| 33 | 880.4 KB |
| 011 Example 6_ construction assignment.mp4 | 20.6 MB |
| 34 | 419.5 KB |
| 002 MINLP_ Pyomo (Couenne).mp4 | 19.4 MB |
| 35 | 643.7 KB |
| 33434408-winglpk-4.65.zip | 19.2 MB |
| 36 | 830.9 KB |
| 33434418-winglpk-4.65.zip | 19.2 MB |
| 37 | 830.9 KB |
| 001 Congratulation.mp4 | 19.2 MB |
| 38 | 834.1 KB |
| 006 Example 1_ investiment.mp4 | 18.9 MB |
| 39 | 97.8 KB |
| 33434416-cbc.zip | 18.8 MB |
| 40 | 170.1 KB |
| 33434420-couenne.zip | 18.8 MB |
| 41 | 170.1 KB |
| 33434404-cbc.zip | 18.8 MB |
| 42 | 170.1 KB |
| 005 Pandas.mp4 | 18.2 MB |
| 43 | 826.7 KB |
| 002 Check the solver progress.mp4 | 18.0 MB |
| 44 | 34.0 KB |
| 005 MINLP_ Genetic Algorithm.mp4 | 17.7 MB |
| 45 | 338.5 KB |
| 003 NonConvex Quadratic Programming.mp4 | 16.5 MB |
| 46 | 512.5 KB |
| 004 Numpy.mp4 | 15.9 MB |
| 47 | 52.2 KB |
| 003 MINLP_ Pyomo (decomposition using mindtpy).mp4 | 15.3 MB |
| 48 | 686.7 KB |
| 004 Define a Time Limit.mp4 | 14.3 MB |
| 49 | 760.8 KB |
| 001 Installing Python.mp4 | 13.9 MB |
| 50 | 101.7 KB |
| 003 IDE Spyder.mp4 | 13.8 MB |
| 51 | 201.7 KB |
| 001 Introduction.mp4 | 13.5 MB |
| 52 | 532.7 KB |
| 003 Functions.mp4 | 12.7 MB |
| 53 | 293.9 KB |
| 006 Working with inequality.mp4 | 12.4 MB |
| 54 | 649.5 KB |
| 007 MINLP_ Particle Swarm (PSO).mp4 | 11.8 MB |
| 55 | 224.3 KB |
| 007 LP_ PuLP.mp4 | 11.5 MB |
| 56 | 499.9 KB |
| 002 MILP_ Pyomo.mp4 | 11.1 MB |
| 57 | 934.9 KB |
| 002 NLP_ Pyomo (IPOPT).mp4 | 11.0 MB |
| 58 | 1009.5 KB |
| 007 Graphs.mp4 | 10.5 MB |
| 59 | 557.3 KB |
| 33907232-GA-concepts.pdf | 10.3 MB |
| 60 | 724.5 KB |
| 33108978-Pyomo-Slides-Sandia-National-Laboratories-free-content.pdf | 10.2 MB |
| 61 | 811.6 KB |
| 32608862-Ipopt-3.11.1-win64-intel13.1.zip | 9.9 MB |
| 62 | 109.9 KB |
| 004 Jupyter Notebook_Lab.mp4 | 9.3 MB |
| 63 | 744.4 KB |
| 013 Example 8_ job assignment.mp4 | 8.5 MB |
| 64 | 505.1 KB |
| 003 Type of Variables.mp4 | 8.3 MB |
| 65 | 715.6 KB |
| 003 Pyomo_ Pprint.mp4 | 7.0 MB |
| 66 | 1016.2 KB |
| 014 How to Learn More_.mp4 | 6.5 MB |
| 67 | 530.7 KB |
| 001 LP_ Introduction.mp4 | 6.3 MB |
| 68 | 757.0 KB |
| 009 Rules inside Constraints.mp4 | 6.2 MB |
| 69 | 792.6 KB |
| 007 pyo.summation.mp4 | 6.1 MB |
| 70 | 970.1 KB |
| 001 What is Mathematical Modelling_.mp4 | 5.4 MB |
| 71 | 614.5 KB |
| 003 NLP_ SCIP.mp4 | 5.1 MB |
| 72 | 883.9 KB |
| 004 MILP_ SCIP.mp4 | 5.0 MB |
| 73 | 975.4 KB |
| 008 Which solver and frameworks should we choose_.mp4 | 4.1 MB |
| 74 | 890.1 KB |
| 002 How do we solve optimization problems_.mp4 | 3.8 MB |
| 75 | 185.6 KB |
| 004 MINLP_ SCIP.mp4 | 3.7 MB |
| 76 | 338.3 KB |
| 003 MILP_ Ortools.mp4 | 3.3 MB |
| 77 | 725.7 KB |
| 33912964-Learn-to-Program-with-Python.pdf | 3.3 MB |
| 78 | 737.9 KB |
| 011 WarmStart.mp4 | 3.2 MB |
| 79 | 843.4 KB |
| 001 MILP_ Introduction.mp4 | 3.1 MB |
| 80 | 881.4 KB |
| 002 Framework and Solvers.mp4 | 3.1 MB |
| 81 | 904.3 KB |
| 002 Packages.mp4 | 2.9 MB |
| 82 | 107.3 KB |
| 004 Objective Function and Constraints.mp4 | 2.7 MB |
| 83 | 267.2 KB |
| 001 Introduction.mp4 | 2.7 MB |
| 84 | 298.1 KB |
| 36020656-JobShopSchedulling-Book.pdf | 2.5 MB |
| 85 | 512.0 KB |
| 005 How to model your problem_.mp4 | 2.3 MB |
| 86 | 698.4 KB |
| 33907038-1-LP-concepts.pdf | 2.2 MB |
| 87 | 801.2 KB |
| 33907058-MILP-concepts.pdf | 1.6 MB |
| 88 | 362.1 KB |
| 36258273-Material.pdf | 1.6 MB |
| 89 | 402.7 KB |
| 36258259-Material.pdf | 1.6 MB |
| 90 | 402.7 KB |
| 33108968-Pyomo-Documentation.pdf | 1.6 MB |
| 91 | 439.1 KB |
| 001 NLP_ Introduction.mp4 | 1.5 MB |
| 92 | 490.7 KB |
| 001 MINLP_ Introduction.mp4 | 1.4 MB |
| 93 | 623.3 KB |
| 33907256-PSO-concepts.pdf | 1.4 MB |
| 94 | 652.3 KB |
| 001 Introduction.mp4 | 1.2 MB |
| 95 | 795.9 KB |
| 33907072-NLP-concepts.pdf | 1.2 MB |
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