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An example that I love is the problem where, given distinct $a_1, a_2, \ldots, a_n \in \mathbb{N}$, decide if: $$\int_{-\pi}^{\pi} \cos(a_1 z) \cos(a_2 z) \ldots \cos(a_n z) \, dz \ne 0$$
This at first seems like a continuous problem to evaluate this integral, however it is easy to show that this integral is not zero iff there exists a balanced partition of ...
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There are many continuous problems of the form "test whether this combinatorial input can be realized as a geometric structure" that are complete for the existential theory of the reals, a continuous analogue of NP. In particular, this implies that these problems are NP-hard rather than polynomially solvable. Examples include testing whether a given graph is ...
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In some technical sense you are asking whether $P = NP \cap coNP$. Suppose that $L \in NP \cap coNP$, thus there exists poly-time $F$ and $G$ so that $x \in L$ iff $\exists y: F(x,y)$ and $x \not\in L$ iff $\exists y: G(x,y)$. This can be recast as a minmax characterization by
$f_x(y) = 1$ if $F(x,y)$ and $f_x(y) = 0$ otherwise; $g_x(y) = 0$ if $G(x,y)$ ...
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Here is an example, where one can produce a solution in polynomial time, but evaluating a given solution is NP-hard.
Input: Positive integers $n,k$ (in unary encoding), with $k\leq n$.
Task: Maximize the number of edges in an $n$-vertex graph under the constraint that its maximum clique size is at most $k$.
Solution: It is known from extremal graph ...
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Seymour and Thomas showed a min-max characterization of treewidth. Yet, tree width is NP-hard. This however is not quite the kind of characterization you are asking for, because the dual function $g$ is not a polynomial time computable function of a short certificate. This is most likely unavoidable for NP complete problems, because otherwise we would have ...
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The problem is very similar to Min Uncut. In Min Uncut, given a graph $G = (V, E)$, we need to find a subset of edges $E'$ s.t. $G - E'$ is bipartite; the objective is to minimize the size of $|E'|$. For brevity, let me call you problem $\cal P$ and Min Uncut $\cal U$.
Observation. An instance $G$ of $\cal P$ has a solution of cost 0 if and only if $G$ is ...
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Parity games, Mean-payoff games, Discounted games, and Simple Stochastic games fall within this category.
All of them are infinite two-player zero-sum games played on graphs, where players control vertices and choose where a token should go next. All have equilibria in memoryless positional strategies, meaning that each player chooses an edge at each choice ...
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While this doesn't exactly answer your original question, it's a (conjectural) example of a sort of philosophical counterpoint: a problem where the presentation is discrete but all of the hardness comes from the 'continuous' aspect of the problem.
The problem is the Sum of Square Roots problem: given two sets of integers $A=\{a_1, a_2, \ldots, a_m\}$ and $B=...
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There is a naive algorithm for programs with bounded-size inputs: enumerate all programs in order of increasing length (or execution time, which is a bounded function of the length). If you can prove that the program is equivalent to the original, stop; otherwise keep searching.
This algorithm is sound. In order for it to be complete, you need to be able to ...
answered Mar 11 '14 at 11:24
Gilles 'SO- stop being evil'
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I would rephrase the question as follows:
Consider the function $F$ and the family of functions $F_{a,b}$ defined as
$$F_{a,b}(x) = F(a,b,x) =ax+b.$$
Can we compute $F_{a,b}$ faster than the complexity of $F$?
If yes, given $a$ and $b$, can we algorithmically find such an algorithm?
As babou wrote I think the answer depends on your computation ...
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I don't know of such a page. Most researchers have specific problems that they are interested in working on, and would only want to collaborate on those. If you pick a particular area and focus on developing your expertise and interests in that area, you could potentially reach out to individual researchers working on the same problems as you. For example, I ...
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Add $n-2k$ extra vertices, each connected to all the original vertices with zero-weight edges, and add a large enough number $W$ to each of the original edges to make their weights all positive. Then look for the minimum weight perfect matching.
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As already noted in the comments, the question is based on a misunderstanding; the actual Positivstellensatz is a stronger statement than Artin’s theorem on nonnegative polynomials, and the real Nullstellensatz as stated in the question is indeed its special case.
Other comments asked for lecture notes with a proof of the Positivstellensatz, and as I do not ...
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This problem is in P, it can be reduced to the Minimum cut problem.
The graph construction is as follows - Add a source and a sink vertex. For each vertex $i$, add an edge with cost $w(i)$ from source to $i$ and another edge of cost $s(i)$ from $i$ to sink. Also add edges from $i$ to $j$ of cost $t(i,j)$ for every pair of vertices $i$ and $j$.
The cost of ...
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Mainly, there exist 3 benchmarks to test shop scheduling problems.
Namely they are Taillard, Structured and ORLib benchmarks. These benchmarks have different
goals. The Taillard benchmark is the most
used benchmark in the literature. The benchmark targets permutation flowshop, flowshop, open shop and job shop scheduling problems. For details and download of ...
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Adiabatic quantum computing (AQC) is a computational model (as Peter said in the comments). Compare AQC with other models of computation such as:
circuit-based quantum computing (CBQC)
Adleman-Lipton model (a model for computing using DNA)
Turing machine model (a model where computations are done with symbols on a tape)
One can devise algorithms using ...
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I think the answer to your question is dependent on the exact setting
of your problem, and in particular the representations you intend to
use for $a$, $b$, and $x$, as well as the available elementary
operations on these representations.
What you want to consider is a partial evaluation of the expression
$ax+b$ when $a$ and $b$ are known. As you remarked, ...
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If your FSM is a DFA, then this is the Minimum Consistent DFA Problem, which is well known in the machine learning community. This problem is NP complete
Gold1978 - Complexity of Automaton Identification from Given Data.
The problem is also known to be hard to approximate within any polynomial factor. Indeed it is even hard to find an NFA whose number of ...
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The second smallest cut, and more generally the $k$ smallest cuts, can be found in time polynomial in $k$ and the network size. See:
H. W. Hamacher. An $(K\cdot n^4)$ algorithm for finding the $k$ best cuts in a network. Oper. Res. Lett. 1(5):186–189, 1982, doi:10.1016/0167-6377(82)90037-2.
H. W. Hamacher, J.-C. Picard, and M. Queyranne. On finding the $K$ ...
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[Since I could not edit my comment, I repost it here as an answer]
To determine if a quadratic program (QP) has multiple solutions (so you have to answer "Yes" if the QP has more than one solutions, and "No" if it has one or no solution) can be shown to be NP-complete by modifying the proof on NP-completeness of QP here http://link.springer.com/article/10....
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You might try one of the auction-based algorithms for bipartite matchings. (See e.g. lecture notes describing a simple variant here: https://staff.fnwi.uva.nl/n.s.walton/Notes/Bertsekas_Auction.pdf but more optimizations are possible).
These algorithms do not necessarily have the best worst-case running time, but require only very simple operations, and so ...
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Discrete problems typically tend to be harder (e.g. LP vs. ILP) but it's not the discreteness itself that's the problem... it's how the constraints affect how you can search your domain. For example, you may think that optimizing a polynomial is something that you can do efficiently, but
deciding convexity of quartics (degree-4 polynomials) is NP-hard.
...
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If the cost is $|P_1|+|P_2|+|P_1∩P_2|$, then a simple reduction to the shortest pair edge disjoint paths gives us a polynomial time solution. For each edge $e=(u,v)$ add two edges $(u,uv)$ and $(uv,v)$ each of them with same edge weight as $e$. The shortest pair edge disjoint paths in the new graph corresponds to the required solution in the original graph.
...
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NOTE: My original reduction didn't work. Fixed now.
Can't subset-sum be reduced to this problem fairly easily? Suppose all the profits $v_i$ are the same, say $v_i = 1$, and all the profits $p_i$ are proportional to the weights, so
$p_i = \beta w_i$ with $\beta < 1$.
Now, if there's a set of weights $S$ such that $\sum_{i\in S} w_i = W$, you can get a ...
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I assume the generalization you are thinking of is the following:
Given value $d$, and values $s_i$ and $r_i$ for $i = 1,2,...,k$, find (if possible) an $\alpha$ such that
$$\sum_{i = 1}^k\min(r_i, s_i\alpha) = d$$
Consider the expression $\min(r_i, s_i\alpha)$. This expression is sometimes equal to $r_i$ and sometimes equal to $s_i\alpha$, with a ...
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When n is given and the objective is to minimize d, it is the well-known n-center problem.
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I don't know if you're still interested in this (old) question, and if I understood well the resource constraints you gave in the comment; however it seems that your problem (which is slightly different from usual RCSP problems) is NP-complete for planar (undirected or directed or directed acyclic) graphs of max-degree 3.
The easy reduction is from 3-SAT. ...
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After a failed polynomial-time quick attempt, here it is an idea to prove that it is NP-complete using a reduction from 3SAT.
Given a 3SAT formula with $x_1,...,x_n$ variables and $C_1,...,C_m$ clauses, first build a variable assignment gadget like in the figure below (thanks to @Jukka for the clarifications, the graph drawing style, and the hint for the ...
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This problem is actually related to a scheduling problem knows as "Precedence constrained scheduling to minimize weighted completion time". The problem is as follows : Given a set of jobs, where each job has a processing time (p) and weight (w) and a precedence graph is defined on the jobs. Goal is to schedule the jobs in a single machine (non-preemptive) ...
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