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rorykeeley 2017-04-19 20:20:26 +02:00 committed by GitHub
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jupyter/Linear_Programming.ipynb
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@ -137,7 +137,7 @@
"## Characteristics of a linear program\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/1.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/1.png?raw=true\" >\n",
"</ul> "
]
},
@ -435,7 +435,7 @@
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/19.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/19.png?raw=true\" >\n",
"</ul> \n",
"\n",
"This graphic shows the feasible region for the telephone problem. \n",
@ -450,7 +450,7 @@
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/20.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/20.png?raw=true\" >\n",
"</ul> \n",
"\n",
" To find the optimal solution to the LP, you must find values for the decision variables, within the feasible region, that maximize profit as defined by the objective function. In this problem, the objective function is to maximize \n",
@ -519,7 +519,7 @@
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/22.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/22.png?raw=true\" >\n",
"</ul> \n",
"\n",
"This graphic shows an example of an LP with multiple optimal solutions. This can happen when the slope of the objective function is the same as the slope of one of the constraints, in this case line AB. All the points on line AB are optimal solutions, with the same objective value, because they are all extreme points within the feasible region.\n"
@ -579,7 +579,7 @@
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/26.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/26.png?raw=true\" >\n",
"</ul> \n",
"\n",
"This graphic shows an example of an infeasible constraint set for the telephone production problem. Assume in this case that the person entering data had accidentally entered lower bounds on the production of 1100 instead of 100. The arrows show the direction of the feasible region with respect to each constraint. This data entry error moves the lower bounds on production higher than the upper bounds from the assembly and painting constraints, meaning that the feasible region is empty and there are no possible solutions. "
@ -789,7 +789,7 @@
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/32.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/32.png?raw=true\" >\n",
"</ul> \n"
]
},
@ -812,22 +812,22 @@
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/36.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/36.png?raw=true\" >\n",
"</ul> \n",
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/37.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/37.png?raw=true\" >\n",
"</ul> \n",
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/38.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/38.png?raw=true\" >\n",
"</ul> \n",
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/39.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/39.png?raw=true\" >\n",
"</ul> \n",
"\n",
"\n",
@ -851,7 +851,7 @@
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/42.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/42.png?raw=true\" >\n",
"</ul> \n",
"\n",
"\n",
@ -1094,7 +1094,7 @@
"\n",
"<p>\n",
"<ul>\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/52.png?raw=true \" >\n",
"<img src = \"https://ibmdecisionoptimization.github.io/tutorials/jupyter/training/52.png?raw=true\" >\n",
"</ul> "
]
},