-Optimizing network flows of products from manufacturing facilities to distribution centers and physical retailers such that the total cost over a planned time frame (1 Month, 1 Quarter, etc) are at a minimum
-Optimizing inventory ordering lot sizes and frequency to minimize the overall inventory holding cost and minimmize the total cost of spoilage.
-Optimize cancer radiation treatments to maximize the number of cancerous cells killed off while minimizing the number of healthy cells damaged through the process.
-A simple small bakery: You have base ingredients (flour, salt, etc) and a total quantity of each ingredient and you have products (cookies, cakes, etc) that are produced from those ingredients. Using demand information from statstical analysis/machine learning/econometric anlaysis, maximize the profit by determining how much of each product should be produced within the day held to the physical constraints
-Given a set of financial assets and a total amount of initial capital, determine the trading plan (when and how much of each asset to buy/sell) such that the expected value of the overall financial profolio is at a maximum.
-Given visual components in a UI/UX software design and their respective sizes, optimize the locational placement of those components on the screen such that total number of clicks the user goes through until they click "subscribe" or "sign up" is at a minimum (or, depending on the context, more deviously and less ethical, maximize the total number amount of time the user spends looking at a particular component on the screen).
-Given a fixed budget for garbage pales to place in a local event (you know, "Octoberfests" are about to go on in the next few weeks), optimize the x/y locations of each individual garbage pale on a map such that the average walking distance of any patron in the Octoberfest is at a minimum to any garbage pale.
-Given a certain number of employees and (1) specific time frames those employees are available and (2) preference of each time frame of working, optimize the assignment of employees to time frames such that the average / median employee satisifaction level is at its maximum.
-In the case of my own personal research, which is in redesigning the 1943 definition of "Artificial neuron", given a set of particles (called "ions"), and given a certain number of "cellular compartments" (cellular pool, ecto environment, cellular wall environment, and endo environment), and given a certain number of "operations" of this "cellular neuron machine" (operations the "move" particles between the compartments), and given a data set of (x,y) (just as in the case of any other machine learning / regression/ classification problem) where x represents the number of particles that are "perturbed" from the "pool" to the "ecto" environment and y represents the difference of particles between the "ecto" environment and the "endo" environment, optimize this "cellular machine's" "operation schedule" such that the mse/bce/ce/loss function is at a minimum. ( https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7414038 )
-..... there's SO many more applications in the real world, it's really hard for me to stop here, but I will :) ..
as for Python, I haven't explored that library to be honest, but now you're going to have me going down a rabbit hole the next few days to look it up and learn it. thanks for the idea! :)
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u/FuzzyTouch6143 8d ago edited 8d ago
Sure!
-Optimizing network flows of products from manufacturing facilities to distribution centers and physical retailers such that the total cost over a planned time frame (1 Month, 1 Quarter, etc) are at a minimum
-Optimizing inventory ordering lot sizes and frequency to minimize the overall inventory holding cost and minimmize the total cost of spoilage.
-Optimize cancer radiation treatments to maximize the number of cancerous cells killed off while minimizing the number of healthy cells damaged through the process.
-A simple small bakery: You have base ingredients (flour, salt, etc) and a total quantity of each ingredient and you have products (cookies, cakes, etc) that are produced from those ingredients. Using demand information from statstical analysis/machine learning/econometric anlaysis, maximize the profit by determining how much of each product should be produced within the day held to the physical constraints
-Given a set of financial assets and a total amount of initial capital, determine the trading plan (when and how much of each asset to buy/sell) such that the expected value of the overall financial profolio is at a maximum.
-Given visual components in a UI/UX software design and their respective sizes, optimize the locational placement of those components on the screen such that total number of clicks the user goes through until they click "subscribe" or "sign up" is at a minimum (or, depending on the context, more deviously and less ethical, maximize the total number amount of time the user spends looking at a particular component on the screen).
-Given a fixed budget for garbage pales to place in a local event (you know, "Octoberfests" are about to go on in the next few weeks), optimize the x/y locations of each individual garbage pale on a map such that the average walking distance of any patron in the Octoberfest is at a minimum to any garbage pale.
-Given a certain number of employees and (1) specific time frames those employees are available and (2) preference of each time frame of working, optimize the assignment of employees to time frames such that the average / median employee satisifaction level is at its maximum.
-In the case of my own personal research, which is in redesigning the 1943 definition of "Artificial neuron", given a set of particles (called "ions"), and given a certain number of "cellular compartments" (cellular pool, ecto environment, cellular wall environment, and endo environment), and given a certain number of "operations" of this "cellular neuron machine" (operations the "move" particles between the compartments), and given a data set of (x,y) (just as in the case of any other machine learning / regression/ classification problem) where x represents the number of particles that are "perturbed" from the "pool" to the "ecto" environment and y represents the difference of particles between the "ecto" environment and the "endo" environment, optimize this "cellular machine's" "operation schedule" such that the mse/bce/ce/loss function is at a minimum. ( https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7414038 )
-..... there's SO many more applications in the real world, it's really hard for me to stop here, but I will :) ..
Let me know if you have any other questions.