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Given a class of graphs F, we say that a graph G is universal for F, or F-universal, if every H in F is contained in G as a subgraph. The construction of sparse universal graphs for various families F has received a considerable amount of attention. One is particularly interested in tight F-universal graphs, i.e., graphs whose number of vertices is equal to the largest number of vertices in a graph from F. Arguably, the most studied case is that when F is some class of trees. Given integers n and \Delta, we denote by T(n,\Delta) the class of all n-vertex trees with maximum degree at most \Delta. In this work, we show that every n-vertex graph satisfying certain natural expansion properties is T(n,\Delta)-universal or, in other words, contains every spanning tree of maximum degree at most \Delta. Our methods also apply to the case when \Delta is some function of n. The result has a few very interesting implications. Most importantly, we obtain that the random graph G(n,p) is asymptotically almost surely (a.a.s.) universal for the class of all bounded degree spanning (i.e., n-vertex) trees provided that p \geq c n^{-1/3} \log^2n where c > 0 is a constant. Moreover, a corresponding result holds for the random regular graph of degree pn. In fact, we show that if \Delta satisfies \log n \leq \Delta \leq n^{1/3}, then the random graph G(n,p) with p \geq c \Delta n^{-1/3} \log n and the random r-regular n-vertex graph with r \geq c\Delta n^{2/3} \log n are a.a.s. T(n,\Delta)-universal. Another interesting consequence is the existence of locally sparse n-vertex T(n,\Delta)-universal graphs. For constant \Delta, we show that one can (randomly) construct n-vertex T(n,\Delta)-universal graphs with clique number at most five. Finally, we show robustness of random graphs with respect to being universal for T(n,\Delta) in the context of the Maker-Breaker tree-universality game., Comment: 25 pages

The all-pairs shortest path problem is the first non-artificial problem for which it was shown that adding crossover can significantly speed up a mutation-only evolutionary algorithm. Recently, the analysis of this algorithm was refined and it was shown to have an expected optimization time (w.r.t. the number of fitness evaluations) of $\Theta(n^{3.25}(\log n)^{0.25})$. In contrast to this simple algorithm, evolutionary algorithms used in practice usually employ refined recombination strategies in order to avoid the creation of infeasible offspring. We study extensions of the basic algorithm by two such concepts which are central in recombination, namely \emph{repair mechanisms} and \emph{parent selection}. We show that repairing infeasible offspring leads to an improved expected optimization time of $\mathord{O}(n^{3.2}(\log n)^{0.2})$. As a second part of our study we prove that choosing parents that guarantee feasible offspring results in an even better optimization time of $\mathord{O}(n^{3}\log n)$. Both results show that already simple adjustments of the recombination operator can asymptotically improve the runtime of evolutionary algorithms.