Maximum-flow Algorithms Research Articles (Page 1)

Detecting oriented small objects is a critical task in remote sensing, but the development of high-performance deep learning-based detectors is hindered by the need for large-scale and well-annotated datasets. The high cost of creating these datasets, due to the dense and numerous distribution of small objects, significantly limits the application and development of such detectors. To address this problem, we propose a single-point-based annotation approach (SPA) based on the graph cut method. In this framework, user annotations act as the origin of positive sample points, and a similarity matrix, computed from feature maps extracted by deep learning networks, facilitates an intuitive and efficient annotation process for building graph elements. Utilizing the Maximum Flow algorithm, SPA derives positive sample regions from these points and generates oriented bounding boxes (OBBOXs). Experimental results demonstrate the effectiveness of SPA, with at least a 50% improvement in annotation efficiency. Furthermore, the intersection-over-union (IoU) metric of our OBBOX is 3.6% higher than existing methods such as the “Segment Anything Model”. When applied in training, the model annotated with SPA shows a 4.7% higher mean average precision (mAP) compared to models using traditional annotation methods. These results confirm the technical advantages and practical impact of SPA in advancing small object detection in remote sensing.

We present an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with m edges and polynomially bounded integral demands, costs, and capacities in m 1+ o (1) time. Our algorithm builds the flow through a sequence of m 1+ o (1) approximate undirected minimum-ratio cycles, each of which is computed and processed in amortized m o (1) time using a new dynamic graph data structure. Our framework extends to algorithms running in m 1+ o (1) time for computing flows that minimize general edge-separable convex functions to high accuracy. This gives almost-linear time algorithms for several problems including entropy-regularized optimal transport, matrix scaling, p -norm flows, and p -norm isotonic regression on arbitrary directed acyclic graphs.

A new maximal flow algorithm for solving optimization problems with linguistic capacities and flows

We investigate the application of graph-cut methods for the study of the critical behaviour of the two-dimensional random-field Ising model. We focus on exact ground-state calculations, crossing the phase boundary of the model at zero temperature and varying the disorder strength. For this purpose we employ two different minimum-cut–maximum-flow algorithms, one of augmenting-path and another of push-relabel style. We implement these approaches for the square and triangular lattice problems and compare their computational efficiency.

A framework for the resilience analysis of complex natural gas pipeline networks from a cyber-physical system perspective

Objectives: Finance is the core of the national economy. The development of modern rural economy is inseparable from financial support. The relationship between finance and economic growth has always been one of the hot topics in theoretical research and empirical analysis. Methods: Under the background of the development of Internet e-commerce, the maximum flow algorithm was based on the empirical research on the relationship between China’s financial development and economic growth. Results: Based on this, the two-element discrete choice model of Probit and Logistic for economic growth was constructed. Discrete particle swarm optimization (PSO) algorithm was used to estimate the parameters of the model. The significant degree of the influence factors was calculated. Conclusion: Finally, it was calculated that concurrent business was the decisive factor of economic growth.

Chen, Y.; Li, Z.; Li, P.; Gao, H.; Jin, T.; Du, P., and Zhang, Y., 2020. Evaluation of water resources utilization effectiveness based on eco-economics theory. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 148-150. Coconut Creek (Florida), ISSN 0749-0208.Facing the increasingly severe water resources situation, how to manage water resources reasonably and effectively, and improve the utilization efficiency and efficiency of water resources is an inevitable requirement for the overall development of China's economic and social water resources ecological environment system. Based on this, the effect of water resources utilization is evaluated based on the theory of ecological economics. The SVM correlation model algorithm is proposed. The dynamic analysis and simulation evaluation are carried out through SD simulation technology, and the total system flow diagram of regional water resources utilization evaluation is established. Based on the maximum flow algorithm, the incentive degree of water resources ecological compensation mechanism is studied. InVEST model and household survey are used to calculate the new water conservation and land use conversion costs. After considering the risk of water resources ecosystem loss, the welfare cost method is adopted. On the county scale, the potential objects of ecological compensation for water resources in the Weihe River Basin are identified. The results show that there are obvious spatial differences in water resources ecological compensation efficiency coefficients in Gansu section of Weihe River Basin. Weiyuan County with the highest runoff is 1.26, Gangu County with the lowest runoff is 0.46. The efficiency of the project can be increased by 40.54% after spatial screening of regional compensation objects. Through the evaluation of water resources utilization and water resources policy simulation, it provides a reference for the coordinated development of water resources and social economy in China.

The aerial show of 1,218 drones in the Pyeongchang Winter Olympics was realized by animators drawing up the show with 3D design software in advance and by a central computer determining and assigning onsite which drone will play the role of which pixel in the animation. Manual creation of an animation in which a thousand drones move in harmony without collision is an expensive and difficult task. Thus, we propose a drone simulator to automate this process: given initial and final images, the system samples a given number of initial and final locations of drones, computes collision-free drone paths automatically (each starting from an initial location and arriving at a final location), and visualizes the results as a video. The set of drone paths is optimal in terms of the last arrival time, which is a desirable feature for drone paths.BR We propose two methods of computing the paths: a two-phase algorithm with a collision-removal modification and a single-phase algorithm for cost optimization. The former obtains paths by running a maximum flow algorithm and modifies them to be collision-free.BROn the other hand, the latter computes collision-free paths directly by running a minimum cost maximum flow algorithm with a carefully designed cost assignment. Both sets of output paths have a minimum last arrival time. The single-phase method needs more time than the two-phase method but gives much better values of stretch factor (the ratio of path length to the Euclidean distance between the initial and final locations). This trade-off between computation time and stretch factor is revealed empirically in the performance comparison of the two methods.

With the development of social economy, China’s foreign trade gradually develops into a green and low-carbon development, based on this situation, this paper studies the transformation and upgrading of China’s foreign trade from the perspective of logistics and transportation. This article analyzes various factors that affect the efficiency of foreign trade logistics distribution and the widely used methods of logistics distribution, and gives a logistics and distribution reference model suitable for the current situation of e-commerce in our country, proposes a reference model of e-commerce logistics distribution system based on Internet environment and designs a suitable transportation route selection model and algorithm for distribution center. After testing, the algorithm in this paper is suitable for practical work, and the algorithm has important reference value for designing and improving the logistics and distribution system and improving the delivery efficiency.

In this paper, we focus on the dynamic traffic assignment (DTA) problem on large-scale expressway networks especially under the condition of traffic events (such as severe weather, large traffic accidents etc.). We formulate the expressway network DTA problem as a nonconvex optimization problem. Considering the difficulty of solving the problem, we put forward an approximate solution algorithm based on the network flow theory with high computational efficiency and strong applicability. Specifically, a machine learning approach and a series of customization strategies of network flow model (including multi-origin and multidestination split, flow discretization and parallel edges addition methods) are proposed to transform the DTA problem into a resoluble network flow problem. After that, in order to improve the operational efficiency of an expressway network after traffic events occurring, the proposed network flow based two-layer DTA model (NTDM) is separated into two parts-traffic flow limitation model based on maximum flow algorithm and traffic assignment model based on minimum cost flow algorithm. Experiments on real expressway network data in some provinces of China show that our method can make a significant 26.03% reduction in saturation rate in a particular scenario. In efficiency test, the NTDM is at least 600 times faster than the traditional analytic method in a network with thousands of nodes.

<p>In this paper, we solve this problem of finding maximum flow in extended mixed network by Revised preflow-push methods of Goldberg This algorithm completely different algorithm postflow-pull in [15]. However, we share some common theory with [15].</p>

A method of applying network flow analyses during real time power system operation, to provide better network connectivity visualization, is developed and presented. Graph theory network flow analysis is capable of determining the maximum flow that can be transported between two nodes within a directed graph. These network flow algorithms are applied to a graphical representation of a power system topology to determine the minimum number of system branches needed to be lost in order to guarantee disconnecting the two nodes in the system that are selected. The number of system branches that are found serves as an approximate indicator of system vulnerabilities. The method used in these connectivity analyses makes use of well known graph theory network flow maximum flow algorithms, but also introduces a new algorithm for updating an old network flow solution for the loss of only a single system branch. The proposed new algorithm allows for significantly decreased solution time that is desired in a real-time environment. The value of using the proposed method is illustrated by using a detailed example of the 2008 island formation that occurred in the Entergy power system. The method was applied to a recreation of the 2008 event using a 20,000-bus model of the Entergy system to show both the proposed method's benefits as well as practicality of implementation.

With an increasing number of processing elements (PEs) integrated on a single chip, fault-tolerant techniques are critical to ensure the reliability of such complex systems. In current reconfigurable architectures, redundant PEs are utilized for fault tolerance. In the presence of faulty PEs, the physical topologies of various chips may be different, so the concept of virtual topology from network embedding problem has been used to alleviate the burden for the operating systems. With limited hardware resources, how to reconfigure a system into the most effective virtual topology such that the maximum repair rate can be reached presents a significant challenge. In this article, a new approach using a maximum flow (MF) algorithm is proposed for an efficient topology reconfiguration in reconfigurable architectures. In this approach, topology reconfiguration is converted into a network flow problem by constructing a directed graph; the solution is then found by using the MF algorithm. This approach optimizes the use of spare PEs with minimal impacts on area, throughput, and delay, and thus it significantly improves the repair rate of faulty PEs. In addition, it achieves a polynomial reconfiguration time. Experimental results show that compared to previous methods, the MF approach increases the probability to repair faulty PEs by up to 50% using the same redundant resources. Compared to a fault-free system, the throughput only decreases by less than 2.5% and latency increases by less than 4%. To consider various types of PEs in a practical application, a cost factor is introduced into the MF algorithm. An enhanced approach using a minimum-cost MF algorithm is further shown to be efficient in the fault-tolerant reconfiguration of heterogeneous reconfigurable architectures.

The high way with its characteristics of high flow, fast, safe and comfortable, has played an important role in road traffic. In this paper, based on the maximum-flow algorithm, study on the traffic capacity of highway. Firstly, explain the basic theory of highway traffic capacity.Then, focusing on the method of maximum-flow algorithm to calculate the highway capacity, convert it into usable calculation mathematical model, explain the problem and cite an example.Finally,summarized the full text of the research work. The main research achievements and innovation in this paper is studying the highway network capacity from the macro level, use a quantitative study on the highway traffic capacity of the network.

The problem of preemptive scheduling in a real-time multiprocessor computing system with release time/deadline intervals is investigated. Approximate algorithms based on the generalization of a single-processor algorithm of relative priority are developed and compared to the exact maximum flow algorithm. An algorithm has been developed for the case where requests for the tasks occur periodically with given periods. An algorithm for determining the values of the processor performance for which there exists an admissible schedule for a given assembly of tasks with release time/deadline intervals has been developed.

In this paper, A comparative study is made on the determination of maximum flow in a network by Maximal Flow Algorithm and Bounded Variable Simplex Method. We have introduced a technique to find the route of a flow in any iteration of the bounded variable simplex algorithm. Dhaka Univ. J. Sci. 61(1): 19-26, 2013 (January) DOI: http://dx.doi.org/10.3329/dujs.v61i1.15091

Network models are often applied in project management. In Time — Cost Trade-Off time and cost parameters are assigned to the activities. At first it has to decide what kind of technology and resources will be applied, which determine the parameters. Typically there is not only one proper technology for realize the engineering object. In this paper a known time-cost trade-off based on maximal flow algorithm is generalized by integrating the possibility of applying multi-parameters. This algorithm chooses automatically the optimal technology for all the activities in the model.

This paper focuses on the use of different memory strategies to improve multistart methods. A network design problem in which the costs are given by discrete stepwise increasing cost functions of the capacities installed in the edges is used to illustrate the contributions of adaptive memory and vocabulary building strategies. Heuristics based on shortest path and maximum flow algorithms are combined with adaptive memory in order to obtain an approximate solution to the problem in the framework of a multistart algorithm. Furthermore, a vocabulary building intensification mechanism supported by the resolution of a linear program is also explored. Numerical experiments have shown that the proposed algorithm obtained the best known solutions for some instances in the literature. These results show the contribution of each memory component and the effectiveness of their combination.

In this paper, a branch-and-bound method for solving multi-dimensional quadratic 0–1 knapsack problems was studied. The method was based on the Lagrangian relaxation and the surrogate constraint technique for finding feasible solutions. The Lagrangian relaxations were solved with the maximum-flow algorithm and the Lagrangian bounds was determined with the outer approximation method. Computational results show the efficiency of the proposed method for multi-dimensional quadratic 0–1 knapsack problems.

Let $\lambda({\cal N})$ denote the weight of a minimum cut in an edge-weighted undirected network ${\cal N}$, and n and m denote the numbers of vertices and edges, respectively. It is known that $O(n^{2k})$ is an upper bound on the number of cuts with weights less than $k\lambda({\cal N})$, where $k\geq 1$ is a given constant. This paper first shows that all cuts of weights less than $k\lambda({\cal N})$ can be enumerated in $O(m^2n+n^{2k}m)$ time without using the maximum flow algorithm. The paper then proves for $k < \four$ that $n\choose 2$ is a tight upper bound on the number of cuts of weights less than $k\lambda({\cal N})$, and that all those cuts can be enumerated in $O(m^2n+mn^2\log n)$ time.