Welcome! My name’s Josh, and this is where I post about problems that I found interesting enough to take time to experiment with and share with you.
If you are visiting for the first time and would like to view my posts, please note that the math rendering can be a bit finicky depending on your browser’s settings. If you find that things aren’t rendering for you, try changing the MathJax settings in your browsers using the following steps:
1) Right click an equation you’d like to view
2) Select “Math Settings”
3) Select “Math Renderer”
4) Change the setting from your browser’s default to one of the other provided options
- I find that SVG renders pretty high-quality equations on my end in Chrome or similar, so this may work for you too!
Feel free to contact me at the provided email with any questions or comments.
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Transmission Expansion Planning Problem
The primary purpose of the electrical grid is to safely and reliably transport electricity from electrical power generation units to consumers. To this end, electrical grid infrastructure’s primary components consists of several types of power generating units, called “generators,” which use steam, water, wind, solar, fossil fuels, and nuclear energy to create power, in addition to devices which are used for appropriately reducing or increasing voltage as electricity travels to its end destination, lines for transporting the generated energy, and energy storage facilities that allow excess generated energy to be used at a later time. Designation of resources to further developement of grid infrastruture technology is based off of projected demand for energy, whereby improvements are made to existing grid configurations in order to ensure the reliability and safety of the transportation of energy under predicted increased demand.
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Rollout For Constrained Dynamic Programming Applied To The Quadratic Knapsack Problem
Mathematical models which include integer variables are ubiquitous in many contexts of significant importance within scientific inquiry. Such problems typically are empirically seen as much more difficult to solve than similar models containing only continuous, real-valued variables. The primary difficulty of models with integer variables is that their solution spaces explodes combinatorially as the number of decisions to be made increases. Despite mathematical programs with integer variables suffering from the issue of combinatorial explosion resulting from the presence of integer variables, in the case of problems with linear objective functions and constraints, or problems referred to as linear programs (LPs) and mixed-integer linear programs (MILPs), several approaches have been developed for obtaining high-quality solutions very quickly with much success.
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Hello World
First blog post with an equation!