As a comprehensive measure, the error spectrum will be widely used for estimation performance evaluation. However, it's hard to calculate without the error distribution. An approximate algorithm is proposed in thi...
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ISBN:
(纸本)9781479964192
As a comprehensive measure, the error spectrum will be widely used for estimation performance evaluation. However, it's hard to calculate without the error distribution. An approximate algorithm is proposed in this study to solve this problem. Then, how the approximate calculation can be used is illustrated by numerical examples. Finally, the correctness of the algorithm is validated by the simulation results.
Determining the parallel complexity of maximum cardinality matching in bipartite graphs is one of the most famous open problems in parallel algorithm design. The problem is known to be in RNC, but all known fast (poly...
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As a multivariate generalization of the univariate median, projection depth median (PM) is unique, and enjoys a very high breakdown point, much higher than its affine equivariant competitors such as halfspace depth me...
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As a multivariate generalization of the univariate median, projection depth median (PM) is unique, and enjoys a very high breakdown point, much higher than its affine equivariant competitors such as halfspace depth median. Nevertheless, its computation is challenging. Until now PM can only be exactly computed efficiently for bivariate data. In this article, we develop an algorithm to approximate PM in higher dimensions. Some data examples indicate that the proposed algorithm performs well in terms of both accuracy and efficiency. As an application, we investigate the finite sample relative efficiency of PM by utilizing the Matlab implementation of this algorithm.
Fault diagnosis plays an important role on stable applications maintaining in wireless sensor networks (WSNs). Most existing researchers are concerned about the statics nodes-based diagnosis techniques, which are inco...
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Fault diagnosis plays an important role on stable applications maintaining in wireless sensor networks (WSNs). Most existing researchers are concerned about the statics nodes-based diagnosis techniques, which are incompetent to cope with those dynamically occurring faults. In this paper, we propose a novel mechanism isolating fault (IF) nodes that employs the mobile node as a scanner to diagnose the faults in WSNs. The mobile scanner can detect the fault nodes within its communication region by using sniffer. It can also control the transmitting route of nodes by modifying their links. Starting from the base station, the mobile scanner periodically selects and visits all monitoring stations and consequently explores all static nodes in the monitoring area. After detecting a fault node, the mobile scanner will prevent it from connecting to the other normal nodes. We aim at finding the least number of monitoring stations and discovering an optimal route. We first formulate the two research issues to hitting set problem and travel salesperson problem. We then solve these two nondeterministic polynomial time hard problems by proposing an approximate algorithm, weighted, and hierarchical IF, which only uses local information. The mobile scanner makes a decision by weighing both the significance and the priority of nodes level by level. The proposed mechanism IF maintains the stabile service of WSNs in a transparent manner. The simulation results show that our algorithm can effectively isolate fault nodes, alleviate the damages of network corrupting, and hence increase the resilience of WSNs. Copyright (c) 2013 John Wiley & Sons, Ltd.
This paper studies the following problem in stock cutting: when it is required to cut out complicated designs from parent material, it is cumbersome to cut out the exact design or shape, especially if the cutting proc...
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This paper studies the following problem in stock cutting: when it is required to cut out complicated designs from parent material, it is cumbersome to cut out the exact design or shape, especially if the cutting process involves optimization. In such cases, it is desired that, as a first step, the machine cut out a relatively simpler approximation of the original design, in order to facilitate the optimization techniques that are then used to cut out the actual design. This paper studies this problem of approximating complicated designs or shapes. The problem is defined formally first and then it is shown that this problem is equivalent to the Minimal Nested Polygon problem in geometry. Some properties of the problem are then shown and it is demonstrated that the problem is related to the Minimal Turns Path problem in geometry. With these results, an efficient approximate algorithm is obtained for the original stock cutting problem. Numerical examples are provided to illustrate the working of the algorithm in different cases.
In this paper, we develop efficient exact and approximate algorithms for computing a maximum independent set in random graphs. In a random graph G, each pair of vertices are joined by an edge with a probability p, whe...
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In this paper, we develop efficient exact and approximate algorithms for computing a maximum independent set in random graphs. In a random graph G, each pair of vertices are joined by an edge with a probability p, where p is a constant between 0 and 1. We show that a maximum independent set in a random graph that contains n vertices can be computed in expected computation time 2(O(log22 n)). In addition, we show that, with high probability, the parameterized independent set problem is fixed parameter tractable in random graphs and the maximum independent set in a random graph in n vertices can be approximated within a ratio of 2n/2(root log2 n) in expected polynomial time.
Given an edge-distance graph of a set of suppliers and clients, the bottleneck problem is to assign each client to a selected supplier minimizing their maximum distance. We introduce minimum quantity commitments to ba...
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Given an edge-distance graph of a set of suppliers and clients, the bottleneck problem is to assign each client to a selected supplier minimizing their maximum distance. We introduce minimum quantity commitments to balance workloads of suppliers, provide the best possible approximation algorithm, and study its generalizations and specializations. (c) 2005 Wiley Periodicals, Inc.
The problem of finding shortest 0-gentle paths can be stated as follows: given two points p, q on a polyhedral terrain and a slope parameter 0 e (0, n /2), the objective is to find a path joining p and q on the terrai...
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The problem of finding shortest 0-gentle paths can be stated as follows: given two points p, q on a polyhedral terrain and a slope parameter 0 e (0, n /2), the objective is to find a path joining p and q on the terrain which is shortest such that the slope of the path does not exceed 0. In this paper, we introduce some geometric and analysis properties of such paths and answer the question of whether known results of classical shortest paths hold for shortest 0-gentle paths. An algorithm for approximately computing such shortest 0-gentle paths on terrains is presented, where an approximate shortest 0-gentle path joining two points is a 0-gentle path whose length is the infimum of a sequence of that of 0-gentle paths in which they are decreasing. We also show that the sequence of lengths of paths obtained by the proposed algorithm is convergent. The algorithm is implemented in C++ using CGAL and Open GL in some specific circumstances.
In Japan, distribution centers managed by public authorities have been designed to achieve global optimization for efficient logistics and to maintain the Japanese urban environment. From the standpoint of social logi...
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In Japan, distribution centers managed by public authorities have been designed to achieve global optimization for efficient logistics and to maintain the Japanese urban environment. From the standpoint of social logistics, global optimization should be pursued considering both the environment and the efficiency of business logistics. In this study, we propose two nonlinear mathematical programming models for obtaining the optimal number and locations of public distribution centers and elaborate on the algorithm for determining solutions. These models aim at reducing the amount of truck CO2 emissions while minimizing logistics costs, which consist of transportation, delivery and facility operating costs. Our models are applied to the Tokyo metropolitan area. As the result of that, an appropriate policy for the number and locations of public distribution centers is proposed.
Enterprises can promote their products widely and rapidly over Online Social Network (OSN) through viral marketing. Viral marketing means an enterprise gives samples of one product to some individuals in OSN, such tha...
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Enterprises can promote their products widely and rapidly over Online Social Network (OSN) through viral marketing. Viral marketing means an enterprise gives samples of one product to some individuals in OSN, such that the individuals promote the product to their fans and fans' fans. The information about the product diffuses virally over OSN, and enterprise gains great revenue from the sales. An enterprise which produces different types of products, called competitive products, should conduct viral marketing more than one batch to maximize revenue. Since each individual normally purchase one from different types, the earlier batch product occupies more customers than the later batch product. The enterprise should find a seed sets sequence for Multi-Batches Revenue Maximization (MBRM). In this paper, we observe the behavior of individuals promoting and purchasing products is independent, and propose a Multi-Batches Independent Cascade model. We comprehensively study how to select the seed sets sequence with adaptive method. Since MBRM combines Influence Maximization and integer knapsack problem, MBRM is NP-hard and needs to be optimally analyzed with dynamic programming method. We propose a computation framework with an approximation algorithm using price-aware Reach Reverse-set(p-RRset) and a heuristic algorithm. The experiments on four real OSN datasets show the efficiency and effectiveness of our algorithms.
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