Titlebook: ;

營(yíng)養(yǎng)

Minimum Spanning Tree Verification Under Uncertainty,lue. An . of an input item reveals its exact value. If the exact value is equal to the assumed value, we say that the update . the assumed value. We consider verification under uncertainty for the minimum spanning tree (MST) problem for undirected weighted graphs, where each edge is associated with

RAGE

Resection

On Set Expansion Problems and the Small Set Expansion Conjecture,irected simple graph . with integral vertex weights. The goal is to select a set . of maximum weight so that the number of edges with at least one endpoint in . is at most .. Goldschmidt and Hochbaum [.] show that the problem is NP-hard and they give a .-approximation algorithm for the problem. The

Cholagogue

Hadwiger Number of Graphs with Small Chordality, Hadwiger number of a graph is .-hard on co-bipartite graphs, but can be solved in polynomial time on cographs and on bipartite permutation graphs. We also consider a natural generalization of this problem that asks for the largest integer?. such that?. has a minor with?. vertices and diameter at mo

極微小

ANTE

Induced Disjoint Paths in Circular-Arc Graphs in Linear Time,either common vertices nor adjacent vertices (except perhaps their ends) for .. We present a linear-time algorithm that solves . and finds the corresponding paths (if they exist) on circular-arc graphs. For interval graphs, we exhibit a linear-time algorithm for the generalization of . where the pai

Daily-Value

https://doi.org/10.1007/978-3-030-92152-1s for path-width, tree-width, branch-width and rank-width, and gives rise to new width parameters with associated duality theorems. The dense substructures witnessing large width are presented in a unified way akin?to tangles, as orientations of separation systems satisfying certain consistency axio

LINE

溫和女人

https://doi.org/10.1007/978-1-4615-8783-5 in an environment that may change rapidly and unpredictably during the agents’ navigation. We apply recent formulations of time-varying graphs (TVGs) to DMVP, shedding new light on the computational hierarchy . of TVG classes by analyzing them in the context of graph navigation. We provide hardness

mutineer