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3rd International Conference on Knowledge Discovery and Data Mining

作者： He, Jinguo Cent Univ Nationalities Sch Sci Beijing Peoples R China

ISBN: (纸本)9780769539232

Automatic threshold selection is significant in image segmentation, understanding and recognition. Finding global minimum of the histogram is difficult because many algorithms fail to end in a local minimum. A new competitive algorithm is proposed to automatically select threshold based on histogram analysis. Given a random initial value, the new algorithm begins to renew the value towards global minimum without stopping at local minimum by a competitive scheme. With the new algorithm, the briefness, low computation, and stability characteristic of threshold segmentation is reserved.

关键词： threshold selection competitive algorithm histogram

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Implementing TURF analysis through binary linear programming

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FOOD QUALITY AND PREFERENCE 2013年第1期28卷 382-388页

作者： Serra, Daniel Univ Pompeu Fabra Dept Econ & Business Barcelona Spain

This paper introduces the approach of using Total Unduplicated Reach and Frequency (TURF) analysis to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Total Unduplicated Reach and Frequency Market research competitive algorithm Product optimization Large datasets

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Optimality and competitiveness of exploring polygons by mobile robots

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INFORMATION AND COMPUTATION 2011年第1期209卷 74-88页

作者： Czyzowicz, Jurek Labourel, Arnaud Pelc, Andrzej Univ Provence Lab Informat Fondamentale F-13453 Marseille France Univ Quebec Outaouais Dept Informat Gatineau PQ J8X 3X7 Canada

A mobile robot, represented by a point moving along a polygonal line in the plane, has to explore an unknown polygon and return to the starting point;The robot has a sensing area which can be a circle or a square centered at the robot. This area shifts while the robot moves inside the polygon, and at each point of its trajectory the robot "sees" (explores) all points for which the segment between the robot and the point is contained in the polygon and in the sensing area. We focus on two tasks: exploring the entire polygon and exploring only its boundary. We consider several scenarios: both shapes of the sensing area and the Manhattan and the Euclidean metrics. We focus on two quality benchmarks for exploration performance: optimality (the length of the trajectory of the robot is equal to that of the optimal robot knowing the polygon) and competitiveness (the length of the trajectory of the robot is at most a constant multiple of that of the optimal robot knowing the polygon). Most of our results concern rectilinear polygons. We show that optimal exploration is possible in only one scenario, that of exploring the boundary by a robot with square sensing area, starting at the boundary and using the Manhattan metric. For this case we give an optimal exploration algorithm, and in all other scenarios we prove impossibility of optimal exploration. For competitiveness the situation is more optimistic: we show a competitive exploration algorithm for rectilinear polygons whenever the sensing area is a square, for both tasks, regardless of the metric and of the starting point. Finally, we show a competitive exploration algorithm for arbitrary convex polygons, for both shapes of the sensing area, regardless of the metric and of the starting point. (C) 2010 Elsevier Inc. All rights reserved.

关键词： competitive algorithm Mobile robot On-line exploration Polygon

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A revised algorithm for searching for all defective edges in a graph

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DISCRETE APPLIED MATHEMATICS 2011年第18期159卷 2266-2268页

作者： Chen, Ting Zhejiang Gongshang Univ Coll Stat & Math Hangzhou Zhejiang Peoples R China

We consider the following generalization of the classical group testing problem. Given a graph G = (V. E), which contains d defective edges, we want to identify all defective edges in G by testing whether an induced subgraph contains a defective edge or not. Recently, Hwang gave a competitive algorithm to identify all defective edges in a graph with d unknown. We will show an obvious mistake in the algorithm and propose a revised algorithm to solve the problem of searching for all defective edges in a graph. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Group testing Graph testing competitive algorithm

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A competitive algorithm in searching for many edges in a hypergraph

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DISCRETE APPLIED MATHEMATICS 2007年第4期155卷 566-571页

作者： Chen, Ting Hwang, Frank K. Zhejiang Gongshang Univ Coll Stat & Math Hangzhou Peoples R China Natl Chiao tung Univ Dept Appl Math Hsinchu Taiwan

We give a competitive algorithm to identify all d defective edges in a hypergraph with d unknown. Damaschke did the d = 1 case for 2-graphs, Triesch extended the d = 1 case to r-graphs, and Johann did the general d case for 2-graphs. So ours is the first attempt to solve the searching for defective edges problem in its full generality. Further, all the above three papers assumed d known. We give a competitive algorithm where d is unknown. (c) 2006 Elsevier B.V. All rights reserved.

关键词： competitive algorithm hypergraph edge-searching problem group testing graph searching

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Large Scale Global Optimization using Self-adaptive Differential Evolution algorithm

Large Scale Global Optimization using Self-adaptive Differen...

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2010 IEEE World Congress on Computational Intelligence

作者： Brest, Janez Zamuda, Ales Fister, Iztok Maucec, Mirjam Sepesy Univ Maribor Fac Elect Engn & Comp Sci SLO-2000 Maribor Slovenia

ISBN: (纸本)9781424481262

In this paper we present self-adaptive differential evolution algorithm jDElsgo on large scale global optimization. The experimental results obtained by our algorithm on benchmark functions provided for the CEC 2010 competition and special session on Large Scale Global Optimization are presented. The experiments were performed on 20 benchmark functions with high dimension D = 1000. Obtained results show that our algorithm performs highly competitive in comparison with the DECC-G*, DECC-G and MLCC algorithms.

关键词： adaptive control benchmark function competitive algorithm competitive algorithms evolutionary computation jDElsgo algorithm large scale global optimization optimisation self-adaptive control mechanism self-adaptive differential evolution algorithm

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A competitive algorithm to find all defective edges in a graph

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DISCRETE APPLIED MATHEMATICS 2005年第3期148卷 273-277页

作者： Hwang, FK Natl Chiao Tung Univ Dept Math Appl Hsinchu Taiwan

Consider a graph G (V, E) where a subset D E E is called the set of defective edges. The problem is to identify D with a small number of edge tests, where an edge test takes an arbitrary subset S and asks whether the subgraph G(S) induced by S intersects D (contains a defective edge). Recently, Johann gave an algorithm to find all d defective edges in a graph assuming d D I is known. We give an algorithm with d unknown which requires at most d([log(2) vertical bar E vertical bar] + 4) + 1 tests. The information-theoretic bound, knowing d, is about d log(2) (vertical bar E vertical bar/d). For d fixed, our algorithm is competitive with coefficient 1. (c) 2005 Elsevier B.V. All rights reserved.

关键词： group testing graph testing competitive algorithm

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An on-line Multi-CBR agent dispatching algorithm

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SOFT COMPUTING 2007年第1期11卷 1-5页

作者： Li, Yan Wang, Xi-Zhao Ha, Ming-Hu Hebei Univ Coll Math & Comp Baoding 071002 Hebei Peoples R China

Case-based reasoning (CBR) is an effective and fast problem-solving methodology, which solves new problems by remembering and adaptation of past cases. With the increasing requests for useful references for all kinds of problems and from different locations, keeping a single CBR system seems to be outdated and not practical. Multi-CBR agents located in different places are of great support to fast meet these requests. In this paper, the architecture of a multi-CBR agent system is proposed, where the CBR agents locate at different places, and are assumed to have the same ability to deal with new problem independently. When the requests in a request queue from different places are coming one by one, we propose a new policy of dispatching which agent to satisfy the request queue. Throughout the paper, we assume that the system must solve the coming request by considering only past requests. In this context, the performance of traditional greedy algorithms is not satisfactory. We apply a new but simple approach - competitive algorithm for on-line problem (called On-line multi-CBR agent dispatching algorithm) to determine the dispatching policy to keep comparative low cost. The corresponding on-line dispatching algorithm is proposed and the competitive ratio is given. Based on the competitive algorithm, the dispatching of multi-CBR agents is optimized.

关键词： CBR multi-CBR agent on-line problem competitive algorithm

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On-line multi-CBR agent dispatching

On-line multi-CBR agent dispatching

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International Conference on Machine Learning and Cybernetics

作者： Li, Y Wang, XZ Ha, MH Hebei Univ Fac Math & Comp Sci Baoding 071002 Hebei Peoples R China

ISBN: (纸本)0780378652

It is well known that CBR is a fast and efficient problem-solving technique. However, keeping a single CBR system seems to be outdated and not practical. With the increasing requests for useful references for all kinds of problems and from different locations, multi-CBR agents located in different places are of great support to fast meet these requests. In this paper, first, a multi-CBR agents system is proposed. In this system, each CBR agent locates at different places, and is assumed to have the same ability to deal with new case (problem) independently. Next, when requests in a request queue from different places are coming one by one, we propose a new policy of dispatching which agent to orderly satisfy the request queue. In the whole paper, we assume that the system must solve one request by considering only past requests. In this context, the performance of a kind of greedy algorithm is not satisfied. We apply a new but simple approach -competitive algorithm for on-line problem (called ODAL) to decide the dispatching policy from the aspect of keeping comparative low cost. The corresponding on-line dispatching algorithm is proposed and the competitive ratio is given, based on which the dispatching of multi-CBR agents is optimized.

关键词： CBR multi-CBR agent on-line problem competitive algorithm

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Multicast routing, load balancing, and wavelength assignment on tree of rings

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IEEE COMMUNICATIONS LETTERS 2002年第2期6卷 79-81页

作者： Jia, XH Hu, XD Ruan, L Sun, JH City Univ Hong Kong Dept Comp Sci Kowloon Hong Kong Peoples R China Chinese Acad Sci Inst Appl Math Beijing Peoples R China Iowa State Univ Dept Comp Sci Ames IA USA Univ Minnesota Dept Comp Sci & Engn Minneapolis MN USA

There are two steps to establish a multicast connection in WDM networks: routing and wavelength assignment. Shortest path tree (SPT) and Minimum spanning tree (MST) are the two widely used multicast routing methods. The SPT method minimizes the delay from the source to every destination along a routing tree, and the MST method is often used to minimize the network cost of the tree. Load balancing is an important objective in multicast routing, which minimizes the maximal link load in the system. The objective of wavelength assignment is to minimize the number of wavelengths used in the system. This paper analyzes the performance of the Sshortest path tree (SPT) and minimum spanning tree (MST) methods in the tree of ring networks, regarding the performance criteria such as the delay and network cost of generated routing trees, load balancing, and the number of wavelengths required in the system. We prove that SPT and MST methods can not only produce routing trees with low network costs and short delays, but also have good competitive ratios for load balancing problem (LBP) and wavelength assignment problem (WAP), respectively.

关键词： competitive algorithm multicast routing wavelength assignment

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