NP-hardness of the sorting buffer problem on the uniform metric

AbstractAn instance of the sorting buffer problem (SBP) consists of a sequence of requests for service, each of which is specified by a point in a metric space, and a sorting buffer which can store up to a limited number of requests and rearrange them. To serve a request, the server needs to visit the point where serving a request p following the service to a request q requires the cost corresponding to the distance d(p,q) between p and q. The objective of SBP is to serve all input requests in a way that minimizes the total distance traveled by the server by reordering the input sequence. In this paper, we focus our attention to the uniform metric, i.e., the distance d(p,q)=1 if p≠q, d(p,q)=0 otherwise, and present the first NP-hardness proof for SBP on the uniform metric

Experimental Evaluation of Approximation and Heuristic Algorithms for Maximum Distance-Bounded Subgraph Problems

In this paper, we consider two distance-based relaxed variants of the maximum clique problem (Max Clique), named Maxd-Clique and Maxd-Club for positive integers d. Max 1-Clique and Max 1-Club cannot be efficiently approximated within a factor of n1−ε for any real ε>0 unless P=NP , since they are identical to Max Clique (Håstad in Acta Math 182(1):105–142, 1999; Zuckerman in Theory Comput 3:103–128, 2007). In addition, it is NP -hard to approximate Maxd-Clique and Maxd-Club to within a factor of n1/2−ε for any fixed integer d≥2 and any real ε>0 (Asahiro et al. in Approximating maximum diameter-bounded subgraphs. In: Proc of LATIN 2010, Springer, pp 615–626, 2010; Asahiro et al. in Optimal approximation algorithms for maximum distance-bounded subgraph problems. In: Proc of COCOA, Springer, pp 586–600, 2015). As for approximability of Maxd-Clique and Maxd-Club, a polynomial-time algorithm, called ReFindStar d, that achieves an optimal approximation ratio of O(n1/2) for Maxd-Clique and Maxd-Club was designed for any integer d≥2 in Asahiro et al. (2015, Algorithmica 80(6):1834–1856, 2018). Moreover, a simpler algorithm, called ByFindStar d, was proposed and it was shown in Asahiro et al. (2010, 2018) that although the approximation ratio of ByFindStar d is much worse for any odd d≥3, its time complexity is better than ReFindStar d. In this paper, we implement those approximation algorithms and evaluate their quality empirically for random graphs. The experimental results show that (1) ReFindStar d can find larger d-clubs (d-cliques) than ByFindStar d for odd d, (2) the size of d-clubs (d-cliques) output by ByFindStar d is the same as ones by ReFindStar d for even d, and (3) ByFindStar d can find the same size of d-clubs (d-cliques) much faster than ReFindStar d. Furthermore, we propose and implement two new heuristics, Hclub d for Maxd-Club and Hclique d for Maxd-Clique. Then, we present the experimental evaluation of the solution size of ReFindStar d, Hclub d, Hclique d and previously known heuristic algorithms for random graphs and Erdős collaboration graphs

Demonstrating the undermining of science and health policy after the Fukushima nuclear accident by applying the Toolkit for detecting misused epidemiological methods

It is well known that science can be misused to hinder the resolution (i.e., the elimination and/or control) of a health problem. To recognize distorted and misapplied epidemiological science, a 33-item "Toolkit for detecting misused epidemiological methods" (hereinafter, the Toolkit) was published in 2021. Applying the Toolkit, we critically evaluated a review paper entitled, "Lessons learned from Chernobyl and Fukushima on thyroid cancer screening and recommendations in the case of a future nuclear accident" in Environment International in 2021, published by the SHAMISEN (Nuclear Emergency Situations - Improvement of Medical and Health Surveillance) international expert consortium. The article highlighted the claim that overdiagnosis of childhood thyroid cancers greatly increased the number of cases detected in ultrasound thyroid screening following the 2011 Fukushima nuclear accident. However, the reasons cited in the SHAMISEN review paper for overdiagnosis in mass screening lacked important information about the high incidence of thyroid cancers after the accident. The SHAMISEN review paper ignored published studies of screening results in unexposed areas, and included an invalid comparison of screenings among children with screenings among adults. The review omitted the actual state of screening in Fukushima after the nuclear accident, in which only nodules > 5 mm in diameter were examined. The growth rate of thyroid cancers was not slow, as emphasized in the SHAMISEN review paper; evidence shows that cancers detected in second-round screening grew to more than 5 mm in diameter over a 2-year period. The SHAMISEN consortium used an unfounded overdiagnosis hypothesis and misguided evidence to refute that the excess incidence of thyroid cancer was attributable to the nuclear accident, despite the findings of ongoing ultrasound screening for thyroid cancer in Fukushima and around Chernobyl. By our evaluation, the SHAMISEN review paper includes 20 of the 33 items in the Toolkit that demonstrate the misuse of epidemiology. The International Agency for Research on Cancer meeting in 2017 and its publication cited in the SHAMISEN review paper includes 12 of the 33 items in the Toolkit. Finally, we recommend a few enhancements to the Toolkit to increase its utility

Distance-d independent set problems for bipartite and chordal graphs

The paper studies a generalization of the INDEPENDENT SET problem (IS for short). A distance-d independent set for an integer d≥2 in an unweighted graph G=(V,E) is a subset S⊆V of vertices such that for any pair of vertices u,v∈S, the distance between u and v is at least d in G. Given an unweighted graph G and a positive integer k, the DISTANCE-d INDEPENDENT SET problem (D d IS for short) is to decide whether G contains a distance-d independent set S such that |S|≥k. D2IS is identical to the original IS. Thus D2IS is NP-complete even for planar graphs, but it is in P for bipartite graphs and chordal graphs. In this paper we investigate the computational complexity of D d IS, its maximization version MaxD d IS, and its parameterized version ParaD d IS(k), where the parameter is the size of the distance-d independent set: (1) We first prove that for any ε>0 and any fixed integer d≥3, it is NP-hard to approximate MaxD d IS to within a factor of n1/2−ε for bipartite graphs of n vertices, and for any fixed integer d≥3, ParaD d IS(k) is W[1]-hard for bipartite graphs. Then, (2) we prove that for every fixed integer d≥3, D d IS remains NP-complete even for planar bipartite graphs of maximum degree three. Furthermore, (3) we show that if the input graph is restricted to chordal graphs, then D d IS can be solved in polynomial time for any even d≥2, whereas D d IS is NP-complete for any odd d≥3. Also, we show the hardness of approximation of MaxD d IS and the W[1]-hardness of ParaD d IS(k) on chordal graphs for any odd d≥3

Complexity of the minimum single dominating cycle problem for graph classes

In this paper, we study a variant of the Minimum Dominating Set problem. Given an unweighted undirected graph G=(V,E) of n=|V| vertices, the goal of the Minimum Single Dominating Cycle problem (MinSDC) is to find a single shortest cycle which dominates all vertices, i.e., a cycle C such that for the set V(C) of vertices in C and the set N(V(C)) of neighbor vertices of C, V(G)=V(C)∪N(V(C)) and |V(C)| is minimum over all dominating cycles in G [6], [17], [24]. In this paper we consider the (in)approximability of MinSDC if input graphs are restricted to some special classes of graphs. We first show that MinSDC is still NP-hard to approximate even when restricted to planar, bipartite, chordal, or r-regular (r≥3). Then, we show the (lnn+1)-approximability and the (1-ε)lnn-inapproximability of MinSDC on split graphs under P≠NP. Furthermore, we explicitly design a linear-time algorithm to solve MinSDC for graphs with bounded treewidth and estimate the hidden constant factor of its running time-bound

Approximation Algorithms for the Longest Run Subsequence Problem

We study the approximability of the Longest Run Subsequence problem (LRS for short). For a string S = s_1 ? s_n over an alphabet ?, a run of a symbol ? ? ? in S is a maximal substring of consecutive occurrences of ?. A run subsequence S\u27 of S is a sequence in which every symbol ? ? ? occurs in at most one run. Given a string S, the goal of LRS is to find a longest run subsequence S^* of S such that the length |S^*| is maximized over all the run subsequences of S. It is known that LRS is APX-hard even if each symbol has at most two occurrences in the input string, and that LRS admits a polynomial-time k-approximation algorithm if the number of occurrences of every symbol in the input string is bounded by k. In this paper, we design a polynomial-time (k+1)/2-approximation algorithm for LRS under the k-occurrence constraint on input strings. For the case k = 2, we further improve the approximation ratio from 3/2 to 4/3

Approximation algorithms for the graph orientation minimizing the maximum weighted outdegree

Given a simple, undirected graph G=(V,E) and a weight function w:E→ℤ+, we consider the problem of orienting all edges in E so that the maximum weighted outdegree among all vertices is minimized. It has previously been shown that the unweighted version of the problem is solvable in polynomial time while the weighted version is (weakly) NP-hard. In this paper, we strengthen these results as follows: (1) We prove that the weighted version is strongly NP-hard even if all edge weights belong to the set {1,k}, where k is any fixed integer greater than or equal to 2, and that there exists no pseudo-polynomial time approximation algorithm for this problem whose approximation ratio is smaller than (1+1/k) unless P = NP; (2) we present a new polynomial-time algorithm that approximates the general version of the problem within a ratio of (2−1/k), where k is the maximum weight of an edge in G; (3) we show how to approximate the special case in which all edge weights belong to {1,k} within a ratio of 3/2 for k=2 (note that this matches the inapproximability bound above), and (2−2/(k+1)) for any k≥3, respectively, in polynomial time

Graph orientation with splits

The Minimum Maximum Outdegree Problem (MMO) is to assign a direction to every edge in an input undirected, edge-weighted graph so that the maximum weighted outdegree taken over all vertices becomes as small as possible. In this paper, we introduce a new variant of MMO called the p-Split Minimum Maximum Outdegree Problem (p-Split-MMO) in which one is allowed to perform a sequence of p split operations on the vertices before orienting the edges, for some specified non-negative integer p, and study its computational complexity