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Exploration of a disrupted road network after a disaster with an online routing algorithm

OR SPECTRUM 2021年第1期43卷 289-326页

作者： Reyes-Rubiano, Lorena Voegl, Jana Rest, Klaus-Dieter Faulin, Javier Hirsch, Patrick Univ Nat Resources & Life Sci Inst Prod & Logist Vienna Austria Univ Publ Navarra Inst Smart Cities Pamplona Spain

This paper considers the problem of supporting immediate response operations after a disaster with information about the available road network to reach certain locations. We propose an online algorithm that aims to minimize the route length required by an unmanned aerial vehicle (UAV) to explore the road accessibility of potential victim locations. It is assumed that no information about disruptions in the road network is available at the start of the exploration. The online algorithm applies two movement and three orientation strategies. Additionally, a cutting strategy is used to restrict the search space after new information about the state of single roads is obtained. We consider a road and an aerial network for the movements of the UAV, since it is not necessary to follow the route of a road any longer, if it can be marked as disrupted. In extensive numerical studies with artificial and real-world test instances, it is evaluated for different disruption levels, which combinations of movement and orientation strategies perform best. Additionally, we propose different refuelling strategies for the UAV and present how they differ in the number of refuelling operations and the required additional route length. The results show that an efficient online algorithm can save valuable exploration time.

关键词： Disrupted road network Immediate response operations online algorithm Aerial vehicles for humanitarian operations online exploration strategies Disaster management

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online Adaptive algorithm for scheduling PEV Charging

Online Adaptive Algorithm for scheduling PEV Charging

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IEEE International Conference on Control Applications (CCA)

作者： Arif, Anmar I. Ahamed, T. P. Imthias Malik, N. H. King Saud Univ Coll Engn EE Dept Saudi Aramco Chair Elect Power Riyadh 11421 Saudi Arabia

ISBN: (纸本)9781479915590

Plug-in electric vehicles (PEVs) have been increasing in recent years and are expected to keep growing even more. PEVs are charged by using the electricity from the power grid, which leads to higher electricity demands. If PEVs are charged randomly without proper management, the charging might occur during peak periods. Therefore, the charging could cause severe problems to the power system. One way to mitigate this problem is for utilities to employ time dependent pricing such as Critical Peak Pricing or Real Time Pricing (RTP). This paper presents a Learning Automata (LA) algorithm for scheduling PEV under RTP. To train the algorithm and for a good initial schedule, it is used offline with the previous available data, then the algorithm is used online for the current data. It is shown that for a large fleet of PEVs, it might take a few days to learn the best schedule. However, even during this period, the results are better than unscheduled charging. The paper shows that with a proper scheduling algorithm, we can minimize the charging cost of a large number of PEVs.

关键词： Demand Response Learning Automata online algorithm Plug-in Electric Vehicle Pursuit algorithm Real Time Pricing

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A Space-Efficient One-Pass online SVM algorithm

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International Journal of Computational Geometry and Applications 2024年第1-2期34卷 63-79页

作者： Liu, Yangwei Huang, Ziyun Xu, Jinhui Department of Computer Science and Engineering State University of New York at Buffalo Buffalo NY United States Department of Computer Science and Software Engineering Penn State Erie The Behrend College Erie PA United States

In this paper we consider the problem of training a Support Vector Machine (SVM) online using a stream of data in random order. We provide a fast online training algorithm for general SVM on very large datasets. Based on the geometric interpretation of SVM known as the polytope distance, our algorithm uses a gradient descent procedure to solve the problem. With high probability our algorithm outputs an (ϵ, δ)-approximation result in constant time and space, which is independent of the size of the dataset, where (ϵ, δ)-approximation means that the separating margin of the classifier is almost optimal (with error ≤ ϵ), and the number of misclassified training points is very small (with error ≤ δ). Experimental results show that our algorithm outperforms most of existing online algorithms, especially in the space requirement aspect, while maintaining high accuracy. © 2024 World Scientific Publishing Company.

关键词： online algorithm SVM

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An online Learning algorithm of Support Vector Regression Based on Natural Gradient

An Online Learning Algorithm of Support Vector Regression Ba...

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21st Chinese Control and Decision Conference

作者： Yin Huan-ping Sun Zong-hai S China Univ Tech Coll Automat Sci & Engn Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781424427239

Support vector regression based on the quadratic programming is unfit for the online training and predicting, and this paper proposes an online algorithm of the support vector regression based on the natural gradient. The algorithm resolves the slow convergence of the standard gradient descent method by the plateau phenomenon, and increases learning speed. And its dynamical behavior is proved to be Fisher efficient, implying that it has the same performance as the optimal batch estimation of parameters. The results of experiments show it is an efficient online algorithm of the support vector regression.

关键词： online algorithm Natural Gradient Support Vector Regression

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Pigeonhole Design: Balancing Sequential Experiments from an online Matching Perspective

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MANAGEMENT SCIENCE 2025年第3期71卷 1865-1888, iv-vi页

作者： Zhao, Jinglong Zhou, Zijie Boston Univ Questrom Sch Business Boston MA 02215 USA MIT Operat Res Ctr Cambridge MA 02139 USA

Practitioners and academics have long appreciated the benefits of covariate balancing when they conduct randomized experiments. For web-facing firms running online A/B tests, however, it still remains challenging in balancing covariate information when experimental subjects arrive sequentially. In this paper, we study an online experimental design problem, which we refer to as the online blocking problem. In this problem, experimental subjects with heterogeneous covariate information arrive sequentially and must be immediately assigned into either the control or the treated group. The objective is to minimize the total discrepancy, which is defined as the minimum weight perfect matching between the two groups. To solve this problem, we propose a randomized design of experiment, which we refer to as the pigeonhole design. The pigeonhole design first partitions the covariate space into smaller spaces, which we refer to as pigeonholes, and then, when the experimental subjects arrive at each pigeonhole, balances the number of control and treated subjects for each pigeonhole. We analyze the theoretical performance of the pigeonhole design and show its effectiveness by comparing against two well-known benchmark designs: the matched-pair design and the completely randomized design. We identify scenarios when the pigeonhole design demonstrates more benefits over the benchmark design. To conclude, we conduct extensive simulations using Yahoo! data to show a 10.2% reduction in variance if we use the pigeonhole design to estimate the average treatment effect.

关键词： causal inference experimental design covariate balancing online algorithm

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The semi-online robotic pallet loading problem

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COMPUTERS & OPERATIONS RESEARCH 2025年 174卷

作者： Yao, Shaowen Zhang, Tai Zhang, Hao Qiu, Jian Leng, Jiewu Liu, Qiang Wei, Lijun Guangdong Univ Technol Sch Electromech Engn Key Lab Comp Integrated Mfg Syst Guangzhou 510006 Peoples R China Macau Univ Sci & Technol Macau Inst Syst Engn Taipa 999078 Macao Peoples R China Macau Univ Sci & Technol Collaborat Lab Intelligent Sci & Syst Taipa 999078 Macao Peoples R China

The distributor's online pallet loading problem (DPLP), which involves efficiently packing a set of cuboid boxes with various dimensions and unknown order into a minimum number of given sized pallet, is extensively employed in industrial automation and has recently garnered significant attention from the research community. However, the existing online approaches face challenges due to the unpredictable arrival order of boxes and the requirement for fast processing. To address this issue, we introduce anew variant of DPLP, the online pallet loading problem with buffer area, by introducing a buffer area with a predefined capacity within the stacking region. The arrival boxes are initially positioned within the buffer area until the total number of boxes reaches the maximum capacity of the buffer area, then, the boxes in the buffer area are selected and packed into the pallet. We propose a greedy search heuristic to solve the online DPLP with buffer area. Our approach uses an open space approach to represent the residual space and combine simple and guillotine blocks to generate blocks. By minimizing the amount of waste, we select the appropriate box placement. Extensive experimental tests on classical and practical instances shows that our method improves pallet utilization by more than 15% compared to purely online algorithms. Compared with other state-of-the-art algorithms, our method improves the average improvement by 8%. Moreover, our approach exhibits a certain level of generalizability and holds substantial practical value for real-world applications.

关键词： Pallet loading problem online algorithm Greedy heuristic Buffer area

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online Euclidean Spanners

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ACM TRANSACTIONS ON algorithmS 2025年第1期21卷 1-22页

作者： Bhore, Sujoy Toth, Csaba d. Indian Inst Technol Mumbai India Calif State Univ Northridge Los Angeles CA 91330 USA Tufts Univ Medford MA 02155 USA

In this article, we study the online Euclidean spanners problem for points in Rd. Given a set S of n points in Rd, a t-spanner on S is a subgraph of the underlying complete graph G = (S, (( )), that preserves the pairwise Euclidean distances between points in S to within a factor oft, that is the stretch factor. Suppose we are given a sequence of n points (s1, s2, ... , sn) in Rd, where point s is presented in step i for i = 1, ... , n. The objective of an online algorithm is to maintain a geometric t-spanner on S = {s1, ... , s } for each step i. The algorithm is allowed to add new edges to the spanner when a new point is presented but cannot remove any edge from the spanner. The performance of an online algorithm is measured by its competitive ratio, which is the supremum, over all sequences of points, of the ratio between the weight of the spanner constructed by the algorithm and the weight of an optimum spanner. Here, the weight of a spanner is the sum of all edge weights. First, we establish a lower bound of Q (Y-1 log n/log Y-1) for the competitive ratio of any online (1 + Y)spanner algorithm, for a sequence of n points in 1-dimension. We show that this bound is tight, and there is an online algorithm that can maintain a (1 + Y)-spanner with competitive ratio O (Y-1 log n/log Y-1). Next, we design online algorithms for sequences of points in Rd, for any constant d >= 2, under the L2 norm. We show that previously known incremental algorithms achieve a competitive ratio O(Y-(d+1) log n). However, if the algorithm is allowed to use additional points (Steiner points), then it is possible to substantially improve the competitive ratio in terms of Y. We describe an online Steiner (1 + Y)-spanner algorithm with competitive ratio O(Y(1-d )/2 log n). As a counterpart, we show that the dependence on n cannot be eliminated in dimensions d >= 2. In particular, we prove that any online spanner algorithm for a sequence of n points in Rd under the L2 norm has competitive rat

关键词： Geometric spanner ( 1+Y ) -spanner minimum weight online algorithm

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online Alignment and Addition in Multiterm Floating-Point Adders

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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2025年第4期33卷 1182-1186页

作者： Alexandridis, Kosmas Dimitrakopoulos, Giorgos Democritus Univ Thrace Dept Elect & Comp Engn Xanthi Greece

Multiterm floating-point (FP) addition appears in vector dot-product computations, matrix multiplications, and other forms of FP data aggregation. A critical step in multiterm floating-point addition is the alignment of fractions of the FP terms before adding them. Alignment is executed serially by identifying first the maximum of all exponents and then shifting the fraction of each term according to the difference of its exponent from the maximum one. Contrary to common practice, this work proposes a new online algorithm that splits the identification of the maximum exponent, the alignment shift for each fraction, and their addition to multiple fused incremental steps that can be computed in parallel. Each fused step is implemented by a new associative operator that allows the incremental alignment and addition for arbitrary number of operands. Experimental results show that employing the proposed align-and-add operators for the implementation of multiterm floating-point adders can improve delay or save significant area and power. The achieved area and power savings range between 3% and 23% and between 4% and 26%, respectively.

关键词： Energy efficiency floating-point arithmetic multiterm adders online algorithm Energy efficiency floating-point arithmetic multiterm adders online algorithm

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An online approach for cooperative cache updating and forwarding in mobile edge network

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WIRELESS NETWORKS 2025年第1期31卷 149-163页

作者： Somesula, Manoj Kumar Brahma, Banalaxmi Raju, Mekala Ratna Mothku, Sai Krishna Dr B R Ambedkar Natl Inst Technol Jalandhar Dept Comp Sci & Engn Jalandhar 144008 Punjab India SRM Univ AP Dept Comp Sci & Engn Amaravati 522502 AP India Natl Inst Technol Tiruchirappalli Dept Comp Sci & Engn Tiruchirappalli 620015 Tamil Nadu India

The proliferation of technological advancement in the Internet of Things (IoT) and mobile devices accelerates the need for latency-sensitive multimedia applications. The network operator may charge application vendors to cache their content. Vendors risk losing their user base if users don't receive the expected Quality of Service (QoS), which includes meeting specific delay thresholds for services like video on demand. While multiple content copies can enhance QoS by delivering content quickly, maintaining redundant copies is costly. Therefore, deploying edge servers at edge nodes and caching content is a prominent solution for application vendors. This approach guarantees lower latency, fewer content replicas, and reduced strain on backhaul links. However, the limited cache capabilities of individual edge nodes present challenges, such as efficiently allocating scarce resources to meet user demands. This work addresses the earlier challenges by formulating a cooperative content caching and forwarding problem by placing the various latency-sensitive content to minimize the total cost with resource and deadline constraints. The problem is formulated as an integer linear programming problem for cooperative caching in mobile edge networks to mitigate the total cost to the application vendors. In the absence of content popularity information, an online cooperative caching mechanism is presented to solve the dynamic content request and forwarding problem. Extensive simulations have been performed to illustrate that the proposed online algorithm significantly enhances the performance in terms of the total cost, load on the cloud, hit ratio, time utility, and cache utilization.

关键词： Cooperative caching Mobile edge computing Cost effective online algorithm

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A note on the online hierarchical scheduling for lp-norm load balancing☆

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DISCRETE APPLIED MATHEMATICS 2025年 368卷 45-51页

作者： Qi, Xianglai Lu, Lingfa Zhou, Shiguo Zhengzhou Univ Sch Math & Stat Zhengzhou 450001 Henan Peoples R China

In this paper, we consider the online hierarchical scheduling for load balancing on two identical machines. In the problem, the jobs are available online over list and the objective is to minimize the lp-norm of every machine's load. A best possible online algorithm is designed for this problem. (c) 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Scheduling online algorithm Hierarchical machines

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