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Algorithms to prioritize equipment renewals
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prioritizerenewalsequipmentalgorithms
Problem
I am looking for algorithms to prioritize equipment renewals.
Input: (years since last renewal, cost of renewal, importance of renewal).
Output: An ordering of the equipment according to which it will be renewed.
I do not know if there are any algorithms for this particular problem. If you have any idea how to fit this problem into a more general context, that would be useful too.
A way to rephrase the problem:
You have $n$ pieces of equipment $E_1,\ldots,E_n$. For each piece $E_i$ you have a triple $(\text{age}_i,\text{cost}_i,\text{importance}_i)$. At the beginning of the year you have $X$ amount of money. You want to spend these money in order to minimize the function $\sum_i \text{age}_i\cdot \text{importance}_i$ at the end of the year. So, during the year you have to select a subset $S$ of $\{1,\ldots,n\}$ such that:
$$\sum_{i\in S} \text{cost}_i\le X \text{ (cost constraint)}$$ and the sum $$\sum_{i\in S} \text{age}_i\cdot \text{importance}_i$$ is maximal among all subsets of $\{1,\ldots,n\}$ that satisfy the cost constraint.
Any help?
Input: (years since last renewal, cost of renewal, importance of renewal).
Output: An ordering of the equipment according to which it will be renewed.
I do not know if there are any algorithms for this particular problem. If you have any idea how to fit this problem into a more general context, that would be useful too.
A way to rephrase the problem:
You have $n$ pieces of equipment $E_1,\ldots,E_n$. For each piece $E_i$ you have a triple $(\text{age}_i,\text{cost}_i,\text{importance}_i)$. At the beginning of the year you have $X$ amount of money. You want to spend these money in order to minimize the function $\sum_i \text{age}_i\cdot \text{importance}_i$ at the end of the year. So, during the year you have to select a subset $S$ of $\{1,\ldots,n\}$ such that:
$$\sum_{i\in S} \text{cost}_i\le X \text{ (cost constraint)}$$ and the sum $$\sum_{i\in S} \text{age}_i\cdot \text{importance}_i$$ is maximal among all subsets of $\{1,\ldots,n\}$ that satisfy the cost constraint.
Any help?
Solution
Given the clarification to the question, it is a 0-1 knapsack problem (your knapsack is the money available, the value is the objective function), and look for ways to solve that one, for example following the Wikipedia lead.
Edit: A simple approximate algorithm would be just sort equipment on increasing cost per unit (age * importance), and in that order include each if it fits (doesn't run over maximal cost). In the case of continuous knapsack (i.e., can include a fraction of a item) that strategy is optimal. Should work fine if there are many items, and the data isn't too spread out.
Edit: A simple approximate algorithm would be just sort equipment on increasing cost per unit (age * importance), and in that order include each if it fits (doesn't run over maximal cost). In the case of continuous knapsack (i.e., can include a fraction of a item) that strategy is optimal. Should work fine if there are many items, and the data isn't too spread out.
Context
StackExchange Computer Science Q#9282, answer score: 4
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