22

This is a special case of the Travelling Salesman with Neighborhoods (TSPN) problem. In the general version, the neighborhoods need not all be the same. A paper by Dumitrescu and Mitchell, Approximation algorithms for TSP with neighborhoods in the plane, addresses your question. They give a constant factor approximation algorithm for a slightly more general ...


15

A general rule of thumb is that the more abstract/exotic the mathematics you want to mechanise, the easier it gets. Conversely, the more concrete/familiar the mathematics is, the harder it will be. So (for instance) rare animals like predicative point-free topology are vastly easier to mechanize than ordinary metric topology. This might initially seem a ...


14

It seems to me the pseudo-polynomial time dynamic programming algorithm for Subset Sum problem also works for this problem. For each vertex $v_i$, we compute the set $L_i$ consisting of all possible values of paths ended at $v_i$. Then, we have the recurrence relation: $L_i=\{g(v_i)\}\cup\{x+g(v_i)\mid x\in \bigcup_{j\in prec(i)} L_j\}$. Following a ...


14

Complementary slackness is key in designing primal-dual algorithms. The basic idea is: Start with a feasible dual solution $y$. Attempt to find primal feasible $x$ such that $(x, y)$ satisfy complementary slackness. If step 2. succeeded we are done. Otherwise an obstruction to finding $x$ gives a way to modify $y$ so that the dual objective function value ...


14

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 ...


12

We're interested in additive approximations to #3SAT. i.e. given a 3CNF $\phi$ on $n$ variables count the number of satisfying assignments (call this $a$) up to additive error $k$. Here are some basic results for this: Case 1: $k=2^{n-1}-\mathrm{poly}(n)$ Here there is a deterministic poly-time algorithm: Let $m=2^n-2k = \mathrm{poly}(n)$. Now evaluate $\...


11

Yes, a PTAS for Max-Planar-3-SAT can be constructed by using Brenda Baker's approach. This has been observed, for instance, in Theorem 17 in Pierluigi Crescenzi and LucaTrevisan: "Max NP-completeness made easy" Theoretical Computer Science 28, (1999), Pages 65-79


10

The motivation you state for dealing with undecidability applies to decidable but hard problems as well. If you have a problem that is NP-hard or PSPACE-hard, we will typically have to use some form of approximation (in the broad sense of the term) to find a solution. It is useful to distinguish between different notions of approximation. Numeric ...


10

One paper that gives an answer to this question is Chalermsook, Laekhanukit, & Nanongkai (2013). There are also related works in the context of Fixed Parameter Tractability such as Hajiaghayi, Khandekar, & Kortsarz (2013) and Chitnis, Hajiaghayi, Kortsarz (2013). These hardness results are proven under various assumptions such as ETH or existence of ...


10

The answer to the title question is: it's difficult to simulate a Markov chain with negative transition probabilies. Valiant's reduction uses the Chinese remainder theorem, which requires an exact number, not just an approximation. The JSV algorithm cannot tell you what the permanent of a matrix is modulo 3, for example. The type of reductions you'd need ...


10

If you insist on precise partition, then you need to compute all the balanced partitions of a set of points in the plane by a line (the optimal partition is a Voronoi partition, so the two point sets are separated by a line). Such partitions are known as $k$-sets. The fastest algorithm currently known for this work in $O(n^{4/3} \log n)$ for computing these ...


10

There are many open algorithmic problems. All problems below (other than the last bullet) are NP-hard, so we are interested in the best approximation ratio we can achieve in polynomial time. The following are just a sample: Given a non-negative submodular function on a universe $U$, find a set $A$ of size at most $k$ maximizing $f(A)$. The best known ...


10

One relevant TSP version is "Group TSP". In this problem, the "cities" are divided into groups and the goal is to find a tour that visits each group at least once. This has also been studied on the plane, which is closer to what you describe. Here each group is a closed region of the plane and it suffices to visit one point in the region to cover it. See e....


10

Cormen, Leiserson, Rivest and Stein say that this algorithm that achieves ratio of 2 is tight. They did not exclude the possibility of another algorithm achieving better. Vertex Cover is NP-hard to approximate with a factor better than 1.36: http://annals.math.princeton.edu/wp-content/uploads/annals-v162-n1-p08.pdf Also check the following paper which give ...


9

Alon, Matias, and Szegedy proved that finding the frequency of the most frequent of $n$ items requires $\Omega(n)$ space in the worst case in the streaming model, even if you allow a constant number of passes over the input. Since finding the most frequent item gives you a two-pass algorithm for computing its frequency (find in the first pass, track its ...


9

The Lovász $\vartheta$ function is an efficiently computable function with the property $$ \alpha(G) \leq \vartheta(G) \leq \bar{\chi}(G), $$ where $\alpha$ is independence number and $\bar{\chi}$ is clique cover number. If the bound $\frac{\bar{\chi}(G)}{\alpha(G)} \leq n^{1-\varepsilon}$ were true for some constant $\varepsilon > 0$, then we would have ...


9

If $p$ is constant, then the size of the maximum clique in the $G(n,p)$ model is almost everywhere a constant multiple of $\log n$, with the constant proportional to $\log (1/p)$. (See Bollobás, p.283 and Corollary 11.2.) Changing $p$ should therefore not affect the hardness of planting a clique with $\omega(\log n)$ vertices as long as the clique is too ...


9

This is a combination of comments from me and Chandra Chekuri above, elaborated a bit. As background, if you have a partial matching then its symmetric difference with the optimal matching can be decomposed into disjoint alternating paths (and possibly also some alternating cycles but those can be ignored). Hopcroft–Karp maintains a partial matching as it ...


9

In the Directed Odd Cycle Transversal problem the input is a graph $G$ and the task is to find a smallest set $S$ of vertices such that $G-S$ has no (directed) cycles of odd length. In the parameterized version we are also given an integer $k$ and asked whether a solution of size at most $k$ exists. In this paper we prove that (R1) the problem is W$[1]$-...


8

To complement the other answer: Costello, Shapira and Tetali showed that the expected approximation ration achieved by Johnson's algorithm on a random permutation of the variables is strictly better than $\frac{2}{3}$. Poloczek and Schnitger showed that another randomized version of the algorithm has expected approximation ratio $\frac{3}{4}$, and that the ...


8

I think for getting 1.99-approximation algorithm this paper by Manurangsi and Trevisan, has the current fastest algorithm.


8

Let me first try to summarize what is known about the Greedy Conjecture. Blum, Jiang, Li, Tromp, Yannakakis prove that the Greedy Algorithm gives a 4-approximation, and Kaplan and Shafrir show that it gives a 3.5-approximation for the Shortest Common Superstring problem. A version of the greedy algorithm is known to give a 3-approximation (Blum, Jiang, Li, ...


7

I think you can make the classical local ratio algorithm by Bafna et al. give a $2-o(1)$ approximation on the following family of graphs: Take $G_n$ to be a $K_{n,n}$ (the complete bipertite graph with $n$ vertices on each side), and then delete a single edge. The following shows that the algorithm might output all of the "blue" vertices ($2n-4$ in number) ...


7

Looking at the Goemans–Williamson algorithm in the SOS framework yields no technical advantages: it is exactly the same algorithm and the same ideas are used in the analysis. The only advantages in doing so are: Arguably the algorithm seems less "magical" in that viewpoint, though of course that's a matter of taste. It's a good basic case to get intuition ...


7

Why is it sometimes easier to achieve $\epsilon$-additive accuracy than $\epsilon$-multiplicative? Consider a problem where the objective value OPT is guaranteed to lie in a constant non-negative real interval such as $[0, c]$. For example, the paper you mention is about computing approximation solutions to two-player zero-sum matrix games in which the ...


6

[Steiner tree] remains NP-complete if all edge weights are equal, even if $G$ is a bipartite graph having no edges joining two vertices in $C$ or two vertices in $V-C$. — Garey and Johnson, Computers and Intractability, Freeman, 1979. Citation is to private communication with E. R. Berlekamp.


6

This is answering the title of the question more than its content, but you can also consider "approximations" of the halting problem as algorithms which will give you a correct answer on "almost all" programs. The notion of "almost all" programs only makes sense if your model of computation is optimal (in the same sense that for Kolmogorov's complexity), to ...


6

If one wants to approximate the potential function, then yes, there even exists a fully polynomial-time approximation scheme (FPTAS). See James B. Orlin, Abraham P. Punnen, Andreas S. Schulz: Approximate Local Search in Combinatorial Optimization. SIAM J. Comput. 33(5): 1201-1214 (2004). For some settings though, this is not interesting. For example, for ...


6

Check out https://www.math.ucdavis.edu/~latte/ and the corresponding paper Effective lattice point counting in rational convex polytopes. Jesús A. De Loera, Raymond Hemmecke, Jeremiah Tauzer, Ruriko Yoshida. Journal of Symbolic Computation 2004 38:4, 1273-1302. The algorithm they implement was introduced in A Polynomial Time Algorithm for Counting ...


6

This problem generalizes dominating set: given an unweighted graph, there exists a set of k centers such that all other vertices are at distance 1 from them if and only if there exists a dominating set of size k. Dominating set is hard to approximate with a ratio better than $\ln n$. In the above observation the optimal value for the k-center problem is ...


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