A Spanner for the Day After

We show how to construct $(1+\varepsilon)$-spanner over a set $P$ of $n$ points in $\mathbb{R}^d$ that is resilient to a catastrophic failure of nodes. Specifically, for prescribed parameters $\vartheta,\varepsilon \in (0,1)$, the computed spanner $G$ has $O\bigl(\varepsilon^{-c} \vartheta^{-6} n \log n (\log\log n)^6 \bigr)$ edges, where $c= O(d)$. Furthermore, for any $k$, and any deleted set $B \subseteq P$ of $k$ points, the residual graph $G \setminus B$ is $(1+\varepsilon)$-spanner for all the points of $P$ except for $(1+\vartheta)k$ of them. No previous constructions, beyond the trivial clique with $O(n^2)$ edges, were known such that only a tiny additional fraction (i.e., $\vartheta$) lose their distance preserving connectivity. Our construction works by first solving the exact problem in one dimension, and then showing a surprisingly simple and elegant construction in higher dimensions, that uses the one-dimensional construction in a black box fashion

A Spanner for the Day After

We show how to construct (1+epsilon)-spanner over a set P of n points in R^d that is resilient to a catastrophic failure of nodes. Specifically, for prescribed parameters theta, epsilon in (0,1), the computed spanner G has O(epsilon^{-7d} log^7 epsilon^{-1} * theta^{-6} n log n (log log n)^6) edges. Furthermore, for any k, and any deleted set B subseteq P of k points, the residual graph G B is (1+epsilon)-spanner for all the points of P except for (1+theta)k of them. No previous constructions, beyond the trivial clique with O(n^2) edges, were known such that only a tiny additional fraction (i.e., theta) lose their distance preserving connectivity. Our construction works by first solving the exact problem in one dimension, and then showing a surprisingly simple and elegant construction in higher dimensions, that uses the one dimensional construction in a black box fashion

Optimal Geo-Indistinguishable Mechanisms for Location Privacy

We consider the geo-indistinguishability approach to location privacy, and the trade-off with respect to utility. We show that, given a desired degree of geo-indistinguishability, it is possible to construct a mechanism that minimizes the service quality loss, using linear programming techniques. In addition we show that, under certain conditions, such mechanism also provides optimal privacy in the sense of Shokri et al. Furthermore, we propose a method to reduce the number of constraints of the linear program from cubic to quadratic, maintaining the privacy guarantees and without affecting significantly the utility of the generated mechanism. This reduces considerably the time required to solve the linear program, thus enlarging significantly the location sets for which the optimal mechanisms can be computed.Comment: 13 page

ASAP: An Automatic Algorithm Selection Approach for Planning

Despite the advances made in the last decade in automated planning, no planner out- performs all the others in every known benchmark domain. This observation motivates the idea of selecting different planning algorithms for different domains. Moreover, the planners’ performances are affected by the structure of the search space, which depends on the encoding of the considered domain. In many domains, the performance of a plan- ner can be improved by exploiting additional knowledge, for instance, in the form of macro-operators or entanglements. In this paper we propose ASAP, an automatic Algorithm Selection Approach for Planning that: (i) for a given domain initially learns additional knowledge, in the form of macro-operators and entanglements, which is used for creating different encodings of the given planning domain and problems, and (ii) explores the 2 dimensional space of available algorithms, defined as encodings–planners couples, and then (iii) selects the most promising algorithm for optimising either the runtimes or the quality of the solution plans

Exact algorithms for the order picking problem

Order picking is the problem of collecting a set of products in a warehouse in a minimum amount of time. It is currently a major bottleneck in supply-chain because of its cost in time and labor force. This article presents two exact and effective algorithms for this problem. Firstly, a sparse formulation in mixed-integer programming is strengthened by preprocessing and valid inequalities. Secondly, a dynamic programming approach generalizing known algorithms for two or three cross-aisles is proposed and evaluated experimentally. Performances of these algorithms are reported and compared with the Traveling Salesman Problem (TSP) solver Concorde

Towards Convergence: How to Do Transdisciplinary Environmental Health Disparities Research.

Increasingly, funders (i.e., national, public funders, such as the National Institutes of Health and National Science Foundation in the U.S.) and scholars agree that single disciplines are ill equipped to study the pressing social, health, and environmental problems we face alone, particularly environmental exposures, increasing health disparities, and climate change. To better understand these pressing social problems, funders and scholars have advocated for transdisciplinary approaches in order to harness the analytical power of diverse and multiple disciplines to tackle these problems and improve our understanding. However, few studies look into how to conduct such research. To this end, this article provides a review of transdisciplinary science, particularly as it relates to environmental research and public health. To further the field, this article provides in-depth information on how to conduct transdisciplinary research. Using the case of a transdisciplinary, community-based, participatory action, environmental health disparities study in California's Central Valley provides an in-depth look at how to do transdisciplinary research. Working with researchers from the fields of social sciences, public health, biological engineering, and land, air, and water resources, this study aims to answer community residents' questions related to the health disparities they face due to environmental exposure. Through this case study, I articulate not only the logistics of how to conduct transdisciplinary research but also the logics. The implications for transdisciplinary methodologies in health disparity research are further discussed, particularly in the context of team science and convergence science