4,961 research outputs found

    On two-echelon inventory systems with Poisson demand and lost sales

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    We derive approximations for the service levels of two-echelon inventory systems with lost sales and Poisson demand. Our method is simple and accurate for a very broad range of problem instances, including cases with both high and low service levels. In contrast, existing methods only perform well for limited problem settings, or under restrictive assumptions.\u

    Crowdsourcing in Computer Vision

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    Computer vision systems require large amounts of manually annotated data to properly learn challenging visual concepts. Crowdsourcing platforms offer an inexpensive method to capture human knowledge and understanding, for a vast number of visual perception tasks. In this survey, we describe the types of annotations computer vision researchers have collected using crowdsourcing, and how they have ensured that this data is of high quality while annotation effort is minimized. We begin by discussing data collection on both classic (e.g., object recognition) and recent (e.g., visual story-telling) vision tasks. We then summarize key design decisions for creating effective data collection interfaces and workflows, and present strategies for intelligently selecting the most important data instances to annotate. Finally, we conclude with some thoughts on the future of crowdsourcing in computer vision.Comment: A 69-page meta review of the field, Foundations and Trends in Computer Graphics and Vision, 201

    Exploring anomalies in time

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    Algorithms for Scheduling Problems

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    This edited book presents new results in the area of algorithm development for different types of scheduling problems. In eleven chapters, algorithms for single machine problems, flow-shop and job-shop scheduling problems (including their hybrid (flexible) variants), the resource-constrained project scheduling problem, scheduling problems in complex manufacturing systems and supply chains, and workflow scheduling problems are given. The chapters address such subjects as insertion heuristics for energy-efficient scheduling, the re-scheduling of train traffic in real time, control algorithms for short-term scheduling in manufacturing systems, bi-objective optimization of tortilla production, scheduling problems with uncertain (interval) processing times, workflow scheduling for digital signal processor (DSP) clusters, and many more

    The bi-objective workflow satisfiability problem and workflow resiliency

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    A computerized workflow management system may enforce a security policy, specified in terms of authorized actions and constraints, thereby restricting which users can perform particular steps in a workflow. The existence of a security policy may mean that a workflow is unsatisfiable, in the sense that it is impossible to find a valid plan (an assignment of steps to authorized users such that all constraints are satisfied). Work in the literature focuses on the workflow satisfiability problem, a decision problem that outputs a valid plan if the instance is satisfiable (and a negative result otherwise). In this paper, we introduce the Bi-Objective Workflow Satisfiability Problem (BO-WSP), which enables us to solve optimization problems related to workflows and security policies. In particular, we are able to compute a “least bad” plan when some components of the security policy may be violated. In general, BO-WSP is intractable from both the classical and parameterized complexity point of view (where the parameter is the number of steps). We prove that computing a Pareto front for BO-WSP is fixed-parameter tractable (FPT) if we restrict our attention to user-independent constraints. This result has important practical consequences, since most constraints of practical interest in the literature are user-independent. Our proof is constructive and defines an algorithm, the implementation of which we describe and evaluate. We also present a second algorithm to compute a Pareto front which solves multiples instances of a related problem using mixed integer programming (MIP). We compare the performance of both our algorithms on synthetic instances, and show that the FPT algorithm outperforms the MIP-based one by several orders of magnitude on most instances. Finally, we study the important question of workflow resiliency and prove new results establishing that known decision problems are fixed-parameter tractable when restricted to user-independent constraints. We then propose a new way of modeling the availability of users and demonstrate that many questions related to resiliency in the context of this new model may be reduced to instances of BO-WSP
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