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A note on optimal matching with variable controls using the assignment algorithm

JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS 2001年第3期10卷 455-463页

作者： Ming, K Rosenbaum, PR Univ Penn Wharton Sch Dept Stat Philadelphia PA 19104 USA

The assignment algorithm is an old, well-known, widely implemented, fast, combinatorial algorithm for optimal matching in a bipartite graph. This note proposes a method for using the assignment algorithm to solve the problem of optimal matching with a variable number of controls, in which there is a choice not only of who to select as a control for each treated subject, but also of how many controls to have for each treated subject. The strategy uses multiple copies of treated subjects and sinks with zero cost to absorb extra controls. Also, it is shown that an optimal matching with variable numbers of controls cannot be obtained by starting with an optimal pair matching and adding the closest additional controls. An example involving mortality after surgery in Pennsylvania hospitals is used to illustrate the method.

关键词： assignment algorithm full matching matched sampling minimum cost flow network optimization observational studies variable controls

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A Holding Access-Point assignment algorithm for Wireless Local-Area Networks 9

A Holding Access-Point Assignment Algorithm for Wireless Loc...

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Shigeto Tajima Nobuo Funabiki Sumon Kumar Debnath Teruo Higashino Graduate School of Engineering Science Osaka University Graduate School of Natural Science and Technology Okayama University Graduate School of Information Science and Technology Osaka University

ISBN: (纸本)9781509038237;9781509038220

Nowadays, various types of access-points(APs) and hosts such as dedicated APs, laptop personal computers, and mobile terminals have been used in IEEE802.11 wireless localarea networks(WLANs). As a result, the optimal assignment of holding APs into the network field depending on the host type distribution has become very important to improve the network performance. In this paper, we formulate this holding access-point assignment problem as a combinatorial optimization problem and propose its heuristic algorithm. Because plural non-overlapping channels are available in IEEE802.11 WLANs, we extend the algorithm to finding the channel assignment to the APs such that the total interference among them is minimized. The effectiveness of our proposal is verified through simulations in three instances.

关键词： wireless local-area network holding access-point channel assignment algorithm combinatorial optimization problem

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Feature point tracking combining the Interacting Multiple Model filter and an efficient assignment algorithm

Feature point tracking combining the Interacting Multiple Mo...

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Conference on Visual Communications and Image Processing 2007

作者： Marimon, David Abdeljaoued, Yousri Palacios, Bruno Ebrahimi, Touradi Swiss Fed Inst Technol EPFL Signal Proc Inst CH-1015 Lausanne Switzerland

ISBN: (纸本)9780819466211

An algorithm for feature point tracking is proposed. The Interacting Multiple Model (IMM) filter is used to estimate the state of a feature point. The problem of data association, i.e. establishing which feature point to use in the state estimator, is solved by an assignment algorithm. A track management method is also developed. In particular a track continuation method and a track quality indicator are presented. The evaluation of the tracking system on real sequences shows that the IMM filter combined with the assignment algorithm outperforms the Kalman filter, used with the Nearest Neighbour (NN) filter, in terms of data association performance and robustness to sudden feature point manoeuvre.

关键词： feature point extraction and tracking Interacting Multiple Model filter assignment algorithm track management

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Road Traffic assignment algorithm Based on Computer Vision

Road Traffic Assignment Algorithm Based on Computer Vision

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2023 International Conference on Integrated Intelligence and Communication Systems, ICIICS 2023

作者： Shao, Zhengda Zheng, Jingjing Yue, Guiyang Yang, Yubing Highway Monitoring & Emergency Response Center Ministry of Transport of the P.R.C Beijing China Party School of Hebei Provincial Committee of C.P.C Hebei China

ISBN: (纸本)9798350315455

With the development of social economy, people pay more and more attention to traffic problems. How to reasonably allocate road resources and reduce traffic accidents is a hot topic. The most important thing in road traffic is traffic information. At present, the urban vehicle dispatching in China mainly adopts the management method of combining manual calculation and static planning. Computer vision technology can improve efficiency and save labor costs. Therefore, this paper will use MATLAB software to design the road resource allocation algorithm on the road. First, the concept and significance of road traffic allocation are introduced, and then the concept of computer vision is expounded. On this basis, the road traffic allocation algorithm is studied, and then the performance of the traffic allocation algorithm is tested. The final test results show that the average delay time and road allocation time are short and the allocation accuracy is high. This shows that the road traffic assignment algorithm based on computer vision has good performance. © 2023 IEEE.

关键词： assignment algorithm computer vision road traffic traffic assignment traffic vision

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Automatic Semantic Web Service Discovery based on assignment algorithm

Automatic Semantic Web Service Discovery based on Assignment...

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2010 2nd International Conference on Computer Engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

作者： Yanbin Peng Chunming Wu School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangz College of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781424463473

To discovery right service from service library quickly and precisely is a meaningful research topic. However,the performance of current semantic service discovery methods remains to be improved. This paper proposes an improved semantic web service discovery method based on assignment algorithm,which can convert service discovery problem into assignment problem. A serial experiments illustrate the proposed method can improve precision and recall rate of service discovery.

关键词： web services discovery assignment algorithm

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assignment algorithms for Modeling Resource Contention in Multirobot Task Allocation

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2015年第3期12卷 889-900页

作者： Nam, Changjoo Shell, Dylan A. Texas A&M Univ Dept Comp Sci & Engn College Stn TX 77843 USA

This paper considers multirobot task allocation problems where the estimated costs for performing tasks are interrelated, and the overall team objective need not be a standard sum-of-costs (or utilities) model, enabling straightforward treatment of the additional costs incurred by resource contention. In the model we introduce, a team may choose one of a set of shared resources to perform a task (e.g., several routes to reach a destination), and interference is modeled when multiple robots use the same resource. We show that the general problem is NP-hard, and investigate specialized subinstances with particular cost structures. For the general problem, we describe an exact algorithm which finds an optimal assignment in a reasonable time on small instances. Aiming at larger problems, we turn two particular subinstances, introducing an two algorithms that find assignments quickly even for problems of considerable size, the first being optimal, the second being an approximation algorithm but also producing high-quality solutions with bounded suboptimality. Note to Practitioners-An idealization is made in the vast majority of the task allocation literature: the presumption of task independence. Tasks are never performed in perfect isolation in practice and this paper shows that computing task costs independently, although a prevalent modeling simplification, may be detrimental. Whenever robots use shared resources (e.g., narrow passages, limited communication bandwidth), resource contention and physical interference may cause performance to degrade. These aspects can be thought of as interrelationships between tasks costs and this article introduces an augmented model that expresses such interrelationships by capturing resource-based interactions among robots which change task execution costs. This paper describes optimization methods which allowing different models of contention (e.g., linear or convex) giving the practitioner flexibility for their specific applicatio

关键词： assignment algorithm interference multirobot task allocation resource contention

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Parallel block sparse Bayesian learning for high dimensional sparse signals

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SIGNAL PROCESSING 2025年 233卷

作者： Boyle, Oisin Uney, Murat Yi, Xinping Brindley, Joseph Univ Liverpool Dept Elect Engn & Elect Chadwick BldgPeach St Liverpool L69 7ZF England Southeast Univ Natl Mobile Commun Res Lab Nanjing Jiangsu Peoples R China Gencoa Res & Dev Dept Liverpool L24 8RN England

We address the recovery of block sparse signals by proposing a distributed solution that uses a block-diagonal approximation to the dictionary matrix of the problem. The approximation is found in two stages. First, the Gram matrix of the dictionary matrix is used as a basis for spectral clustering. Afterwards, measurement positions are assigned to the clusters formed from this spectral clustering. The method is then applied to use previous algorithms in the literature of Block Sparse Bayesian Learning in parallel. Moreover, this method also speeds up the algorithm in serial systems. The efficacy of the proposed method is demonstrated in simulations with comparison to the previous Block Sparse Bayesian Learning algorithms.

关键词： Sparse Bayesian Learning Spectral clustering Sparse signal recovery Block sparse model assignment algorithm

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assignment algorithms for Grocery Bill Reduction

Assignment Algorithms for Grocery Bill Reduction

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IEEEE Southeast Conference (SoutheastCon)

作者： Courcy, Melanie Li, Wei Nova Southeastern Univ Coll Comp & Engn Ft Lauderdale FL 33314 USA

ISBN: (纸本)9781665403795

This paper focuses on identifying an algorithm that can be utilized in grocery cost reduction within the consumer space. The algorithm produces the combination of grocery products to stores that net the lowest overall grocery cost for the consumer. This is often referred to as a combinatorial optimization problem, and is commonly used by many industries for resource or task assignment. To identify a solution for grocery cost reduction, the Kuhn-Munkres algorithm (often referred to as the Hungarian algorithm) and the Deepest Hole algorithm are explored in depth. After comparing the algorithms based on their implementation and performance, a third solution combining ideas from the Kuhn-Munkres algorithm and Deepest Hole algorithm was created to solve for the specific needs of this problem. This solution will be referred to as the KMDH Hybrid algorithm. Modifications include the ability for users to select the number of stores they wish to shop at, the ability to use a rectangular grid, and allowing for one-to-many assignments. All three algorithms were developed in Python, and tested on a dataset with a predefined list of stores, products, and prices. It is apparent that the proposed hybrid algorithm can be applied to the assignment problem, and has the potential to be applied to other similar applications.

关键词： assignment algorithm combinatorial optimization Kuhn-Munkres algorithm deepest hole algorithm

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Approximated assignment algorithms for Unordered and Ordered Tasks in Data Shared MEC Systems

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2023年第4期22卷 1968-1987页

作者： Cheng, Siyao Huang, Jiayan Chen, Zhenyue Liu, Jie Li, Jianzhong Harbin Inst Technol Sch Comp Sci & Technol Harbin 150001 Peoples R China

The appearance of Mobile Edge Computing (MEC) successfully solves the bottlenecks of traditional Cloud based networks. Since mobile edges, e.g., base stations, and mobile devices have certain data processing capabilities, it is not necessary to offload all the tasks to the cloud for handling. Therefore, it is quite important to decide the optimal task assignment in MEC systems, and a series of algorithms have been proposed. However, the existing algorithms ignored the data distribution during task assignment, so that their applied ranges are quite limit. Considering the data sharing is quite important in a MEC system, this paper studies task assignment algorithms in Data Shared Mobile Edge Computing Systems in detail. Specifically, three algorithms are proposed to deal with the unordered and ordered holistic tasks respectively. Meanwhile, the situation that the tasks are divisible is also considered, and two algorithms for rearranging the divisible tasks are proposed for different optimization goals. The hardness of the problem, the correctness, complexities, and ratio bounds of the proposed algorithms are analyzed theoretically. Finally, extensive experimental results are carried out. Both theoretical analysis and experiment results show that all the proposed algorithms have high performance in terms of latency, satisfied rate, and energy consumption.

关键词： Mobile edge computing assignment algorithm data shared unordered tasks ordered tasks

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Efficient multisensor fusion using multidimensional assignment for multitarget tracking

Efficient multisensor fusion using multidimensional assignme...

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Signal Processing, Sensor Fusion, and Target Recognition VII

作者： Kirubarajan, T Wang, H Bar-Shalom, Y Pattipati, KR Univ Connecticut Dept Elect & Syst Engn Storrs CT 06269 USA

ISBN: (纸本)081942823X

In this paper we present the development of a multisensor fusion algorithm using multidimensional data association for multitarget tracking. The work is motivated by a large scale ground target surveillance problem, where observations from multiple asynchronous sensors with time-varying sampling intervals (e.g., electronically scanned array radars) are used for centralized fusion. The combination of multisensor fusion with multidimensional assignment is done such as to maximize the "time-depth": in addition to "sensor-width" for the number S of lists handled by the assignment algorithm. The time-depth results from the simultaneous use of multiple frames of measurements obtained at different time instants. The sensor-width comes from the geographically distributed nature of the sensors. A procedure, which guarantees maximum effectiveness for an S-dimensional data association (S greater than or equal to 3), i.e., maximum time-depth (S-1) for each sensor without sacrificing the fusion across sensors, is presented. Using a sliding-window technique (of length S), the estimates are updated after each frame of measurements. The algorithm provides a systematic approach to automatic track formation, maintenance and termination for multitarget tracking using multisensor fusion with multidimensional assignment for data association. Estimation results are presented for simulated data.

关键词： multitarget tracking estimation multisensor fusion data association assignment algorithm multidimensional assignment sensor management

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