In the Set Cover problem we need to cover each item at least once.
I am considering the case in which I want each item to be covered at least $ k $ times with constant $ k $.
I consider the classic LP for the problem and random rounding.
Is it true that the modification of the LP of $ geq 1 $ to $ geq k $ in the coverage restriction and with the same rounding (up to the number of repetitions) also works well for this variant?
It seems so, but I'm not sure if I'm missing something.
How are the vertex-disjoint cycle covers of minimum weight of large dense symmetric graphs in real implementations really calculated?
I know that the problem can be reduced to a general coincidence using the Tutte device or the device suggested by Lovasz and Plummer; However, there is a fly in the ointment with those reductions, namely that each vertex of the original graphic is replicated $ O (n) $ times, producing a match problem for a chart with $ O (n ^ 2) $ vertices and therefore a $ O (n ^ 6) $ algorithmic solution
Question:
These are the devices actually used to calculate the lightest D factors and especially the 2 factors or, if the linear programming formulation provides significantly better performance, resp. footprint and, if so, which variant of linear programming is the most appropriate, primal, dual, primal-dual, etc.
I need an efficient way to generate those cylce covers to investigate the performance of a new idea for a heuristic TSH.
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Take a related Noetherian scheme. Can it be covered by many locally closed irreducible and related related subsystems?
An example: take the 4-dimensional related space on a field and consider the union of two interesting planes at a single point, a cover is {the foreground, the background minus a line passing through the point of intersection, the line that passes through the intersection point minus the intersection point}.
I have a fixed browser that I created in React, but when I click on a link, the window scrolls too much and the browser covers the top of the content. I have tried to dynamically calculate the height of the navigation and take this into account in the displacement, but it still goes to the wrong position.
import react from & # 39; react & # 39;
import {string} from & # 39; prop-types & # 39;
The FixedNav class extends React.Component {
constructor (accessories) {
super (accessories)
this.handleClick = this.handleClick.bind (this)
}
shouldComponentUpdate (nextProps) {
returns nextProps.navItems! == this.props.navItems
}
handleClick on (e) {
const nav = document.querySelector (& # 39; # fixedNav & # 39;)
we go to navHeight = nav.getBoundingClientRect (). height
leave itemLink = document.querySelector (e.target.parentElement.dataset.link)
leave scrollHeight = itemLink.offsetTop - navHeight
window.scroll (0, scrollHeight)
window.location.hash = e.target.parentElement.dataset.link
e.preventDefault ()
}
createNavItems () {
const {navItems} = this.props
returns navItems.map ((item, key) => {
const itemLink = items[1].link
he came back (
{ articles[0] }
)
})
}
render () {
const navItems = this.createNavItems ()
he came back (
)
}
}
FixedNav.propTypes = {
Nav Articles: string.isRequired
}
default export FixedNav
I wonder about the following decision problem:
Instance: we consider a $ n times p $ matrix $ M $ of zeros and ones, and two integers. $ N $ Y $ k $.
Question: Is it possible to cover all of the matrix with $ N $ side length squares $ k $?
It is possible that the squares cover some of the zeros in the matrix and that they can overlap each other.
I have the impression that it is $ textsf {NP} $-complete (it is clear $ textsf {NP} $), I find some similarities with the grid that covers rectangles, but I can not find a good reduction.
Can I get any idea about the problem?
Thank you.
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I have three covers of electronic books that I need to be designed. Please send me a PM for your cost for coverage and samples of your work.
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