The hardness of perfect phylogeny, feasible register assignment and other problems on thin colored graphs

AbstractIn this paper, we consider the complexity of a number of combinatorial problems; namely, Intervalizing Colored Graphs (DNA physical mapping), Triangulating Colored Graphs (perfect phylogeny), (Directed) (Modified) Colored Cutwidth, Feasible Register Assignment and Module Allocation for graphs of bounded pathwidth. Each of these problems has as a characteristic a uniform upper bound on the tree or path width of the graphs in “yes”-instances. For all of these problems with the exceptions of Feasible Register Assignment and Module Allocation, a vertex or edge coloring is given as part of the input. Our main results are that the parameterized variant of each of the considered problems is hard for the complexity classes W[t] for all t∈N. We also show that Intervalizing Colored Graphs, Triangulating Colored Graphs, and Colored Cutwidth are NP-Complete

On the Parameterized Complexity of the Perfect Phylogeny Problem

This paper categorizes the parameterized complexity of the algorithmic problems Perfect Phylogeny and Triangulating Colored Graphs when parameterized by the number of genes and colors, respectively. We show that they are complete for the parameterized complexity class XALP using a reduction from Tree-chained Multicolor Independent Set and a proof of membership. We introduce the problem Triangulating Multicolored Graphs as a stepping stone and prove XALP-completeness for this problem as well. We also show that, assuming the Exponential Time Hypothesis, there exists no algorithm that solves any of these problems in time $f(k) n^{o(k)}$, where $n$ is the input size, $k$ the parameter, and $f$ any computable function

A list of parameterized problems in bioinformatics

In this report we present a list of problems that originated in bionformatics. Our aim is to collect information on such problems that have been analyzed from the point of view of Parameterized Complexity. For every problem we give its definition and biological motivation together with known complexity results.Postprint (published version

Characterizing Hardness in Parameterized Complexity

Parameterized complexity theory relaxes the classical notion of tractability and allows to solve some classically hard problems in a reasonably efficient way. However, many problems of interest remain intractable in the context of parameterized complexity. A completeness theory to categorize such problems has been developed based on problems on circuits and Model Checking problems. Although a basic machine characterization was proposed, it was not explored any further. We develop a computational view of parameterized complexity theory based on resource-bounded programs that run on alternating random access machines. We develop both natural and normalized machine characterizations for the W[t] and L[t] classes. Based on the new characterizations, we derive the basic completeness results in parameterized complexity theory, from a computational perspective. Unlike the previous cases, our proofs follow the classical approach for showing basic NP-completeness results (Cook's Theorem, in particular). We give new proofs of the Normalization Theorem by showing that (i) the computation of a resource-bounded program on an alternating RAM can be represented by instances of corre- sponding basic parametric problems, and (ii) the basic parametric problems can be decided by programs respecting the corresponding resource bounds. Many of the fundamental results follow as a consequence of our new proof of the Normalization Theorem. Based on a natural characterization of the W[t] classes, we develop new structural results establishing relationships among the classes in the W-hierarchy, and the W[t] and L[t] classes. Nontrivial upper-bound beyond the second level of the W-hierarchy is quite uncommon. We make use of the ability to implement natural algorithms to show new upper bounds for several parametric problems. We show that Subset Sum, Maximal Irredundant Set, and Reachability Distance in Vector Addition Systems (Petri Nets) are in W[3], W[4], and W[5], respectively. In some cases, the new bounds result in new completeness results. We derive new lower bounds based on the normalized programs for the W[t] and L[t] classes. We show that Longest Common Subsequence, with parameter the number of strings, is hard for L[t], t >= 1, and for W[SAT]. We also show that Precedence Constrained Multiprocessor Scheduling, with parameter the number of processors, is hard for L[t], t >= 1

LIPIcs, Volume 251, ITCS 2023, Complete Volume

LIPIcs, Volume 251, ITCS 2023, Complete Volum

LIPIcs, Volume 261, ICALP 2023, Complete Volume

LIPIcs, Volume 261, ICALP 2023, Complete Volum