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International Conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： Gaurav Khare Nikhil Sahu R Sunitha Dept. of Electrical Engineering National Institute of Technology Calicut Kozhikode Kerala India Dept. of EEE Rajiv Gandhi Proudyogiki Vishwavidyalaya Bhopal Madhya Pradesh India

Power system state estimation with exclusive utilization of synchronous phasor measurements demands that the system should be completely observable through PMUs only. To have minimum number of PMUs, the PMU placement issue in any network is an optimization problem. In this paper, a model for the optimal placement of phasor measurement units (PMUs) in electric power networks is presented. Optimal measurement set is determined to achieve full network observability during normal conditions, i e no PMU failure or transmission line outage is considered. Observability analysis is carried out using topological observability rules. A connectivity matrix modification based integer linear programming is used as an optimization tool to obtain the minimal number of PMUs and their corresponding locations while satisfying associated constraint . Simulation results for IEEE 30-bus and New England 39-bus test systems are presented and compared with the existing techniques, to justify the effectiveness of proposed method In All investigations, the zero-injected buses are considered to obtain the best answers.

关键词： Phasor measurement units Observability Power systems integer linear programming Transmission line measurements Transmission line matrix methods Power measurement

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Computing subset vertex covers in H-free

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THEORETICAL COMPUTER SCIENCE 2025年 1032卷

作者： Brettell, Nick Oostveen, Jelle J. Pandey, Sukanya Paulusma, Daniel Rauch, Johannes van Leeuwen, Erik Jan Victoria Univ Wellington Wellington New Zealand Univ Utrecht Utrecht Netherlands Rhein Westfal TH Aachen Aachen Germany Univ Durham Durham England Ulm Univ Ulm Germany

We consider a natural generalization of VERTEX COVER: the SUBSET VERTEX COVER problem, which is to decide for a graph G = (V, E), a subset T C V and integer k, if V has a subset S of size at most k, such that S contains at least one end-vertex of every edge incident to a vertex of T. A graph is H-free if it does not contain H as an induced subgraph. We solve two open problems from the literature by proving that SUBSET VERTEX COVER is NP-complete on subcubic (claw, diamond)-free planar graphs and on 2-unipolar graphs, a subclass of 2P3-free weakly chordal graphs. Our results show for the first time that SUBSET VERTEX COVER is computationally harder than VERTEX COVER (under P not equal NP). We also prove new polynomial time results, some of which follow from a reduction to VERTEX COVER restricted to classes of probe graphs. We first give a dichotomy on graphs where G[T] is H-free. Namely, we show that SUBSET VERTEX COVER is polynomial-time solvable on graphs G, for which G[T] is H-free, if H = sP1 +tP2 and NP-complete otherwise. Moreover, we prove that SUBSET VERTEX COVER is polynomial-time solvable for (sP1 + P2 +P3)-free graphs and bounded mim-width graphs. By combining our new results with known results we obtain a partial complexity classification for SUBSET VERTEX COVER on H-free graphs.

关键词： integer linear programming

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An integer linear programming Model for View Selection on Overlapping Camera Clusters

An Integer Linear Programming Model for View Selection on Ov...

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： Massimo Mauro Hayko Riemenschneider Alberto Signoroni Riccardo Leonardi Luc Van Gool Department of Information Engineering University of Brescia Italia Computer Vision Laboratory ETH Zurich Switzerland K.U. Leuven Belgium

Multi-View Stereo (MVS) algorithms scale poorly on large image sets, and quickly become unfeasible to run on a single machine with limited memory. Typical solutions to lower the complexity include reducing the redundancy of the image set (view selection), and dividing the image set in groups to be processed independently (view clustering). A novel formulation for view selection is proposed here. We express the problem with an integer linear programming (ILP) model, where cameras are modeled with binary variables, while the linear constraints enforce the completeness of the 3D reconstruction. The solution of the ILP leads to an optimal subset of selected cameras. As a second contribution, we integrate ILP camera selection with a view clustering approach which exploits Leveraged Affinity Propagation (LAP). LAP clustering can efficiently deal with large camera sets. We adapt the original algorithm so that it provides a set of overlapping clusters where the minimum and maximum sizes and the number of overlapping cameras can be specified. Evaluations on four different dataset show our solution provides significant complexity reductions and guarantees near-perfect coverage, making large reconstructions feasible even on a single machine.

关键词： Cameras Image reconstruction Three-dimensional displays Clustering algorithms Vectors integer linear programming Complexity theory

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Planning Amidst Uncertainty: Identifying Core CCS Infrastructure Robust to Storage Uncertainty

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ENERGIES 2025年第4期18卷 926-926页

作者： Olson, Daniel Yaw, Sean Montana State Univ Sch Comp Bozeman MT 59717 USA

Carbon Capture and Storage (CCS) is a critical technology for reducing anthropogenic CO2 emissions, but its large-scale deployment is complicated by uncertainties in geological storage performance. These uncertainties pose significant financial and operational risks, as underperforming storage sites can lead to costly infrastructure modifications, inefficient pipeline routing, and economic shortfalls. To address this challenge, we propose a novel optimization workflow that is based on mixed-integer linear programming and explicitly integrates probabilistic modeling of storage uncertainty into CCS infrastructure design. This workflow generates multiple infrastructure scenarios by sampling storage capacity distributions, optimally solving each scenario using a mixed-integer linear programming model, and aggregating results into a heatmap to identify core infrastructure components that have a low likelihood of underperforming. A risk index parameter is introduced to balance trade-offs between cost, CO2 processing capacity, and risk of underperformance, allowing stakeholders to quantify and mitigate uncertainty in CCS planning. Applying this workflow to a CCS dataset from the US Department of Energy's Carbon Utilization and Storage Partnership project reveals key insights into infrastructure resilience. Reducing the risk index from 15% to 0% is observed to lead to an 83.7% reduction in CO2 processing capacity and a 77.1% decrease in project profit, quantifying the trade-off between risk tolerance and project performance. Furthermore, our results highlight critical breakpoints, where small adjustments in the risk index produce disproportionate shifts in infrastructure performance, providing actionable guidance for decision-makers. Unlike prior approaches that aimed to cheaply repair underperforming infrastructure, our workflow constructs robust CCS networks from the ground up, ensuring cost-effective infrastructure under storage uncertainty. These findings demonstrate th

关键词： carbon capture and storage infrastructure design optimization integer linear programming Monte Carlo simulation heat map

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A Robust FPGA Router With Optimization of High-Fanout Nets and Intra-CLB Connections

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 2025年第3期44卷 1003-1016页

作者： Jiang, Xun Wang, Jiarui Mai, Jing Di, Zhixiong Lin, Yibo Peking Univ Sch Integrated Circuits Beijing 100871 Peoples R China Peking Univ Sch Comp Sci Beijing 100871 Peoples R China Univ Elect Sci & Technol China Sch Integrated Circuits Sci & Engn Chengdu 610031 Peoples R China Peking Univ Beijing Adv Innovat Ctr Integrated Circuits Beijing 100871 Peoples R China Peking Univ Inst Elect Design Automat Wuxi 214000 Peoples R China

Routing is the most time-consuming step in the implementation flow of field programmable gate array (FPGA) designs. With the advance in transistor scaling and system integration, hardware resources in FPGA devices are growing in a larger quantity and diversity. The routing architecture is designed to be more complicated for mapping RTL designs to FPGA devices correctly, which brings significant challenges for current FPGA routing algorithms. The key challenges for routing algorithms lie in large solution space and heavy congestion, especially for high-fanout nets (HFNets). We propose a partition-based algorithm to accelerate the routing of HFNets, which decomposes the global routing guide to shrink the search space for connecting each sink. Meanwhile, the congestions existing inside configurable logic block (CLB) are hard to handle by traditional sequential negotiation-based algorithms, because the industrial routing architecture is quite complex. We propose a concurrent intra-CLB rerouting algorithm to effectively resolve routing congestion inside a CLB tile induced by connections between intra-CLB logic pins, e.g., logic elements and switch boxes. Experimental results on modified ISPD2016 benchmarks demonstrate that our framework can achieve 100% routability in 9.8% less wirelength and $11\times $ less runtime, while the state-of-the-art VTR 8.0 routing algorithm fails at 7 of 12 benchmarks.

关键词： Routing Field programmable gate arrays Computer architecture Pins Logic Video recording Partitioning algorithms integer linear programming routing Steiner trees partitioning algorithms

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Mathematical models for the one-dimensional cutting stock problem with setups and open stacks

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2025年第3期49卷 1-35页

作者： Guimaraes, Gabriel Gazzinelli Poldi, Kelly Cristina Martin, Mateus Univ Estadual Campinas UNICAMP Inst Matemat Estat & Computac Cient IMECC Rua Sergio Buarque Holanda 651 BR-13083859 Campinas SP Brazil Univ Fed Sao Carlos UFSCar Dept Engn Prod Rodovia Joao Leme dos Santos Km 110 BR-18052780 Sorocaba SP Brazil

In real-life production, the cutting stock problem is often associated with additional constraints and objectives. Among the auxiliary objectives, two of the most relevant are the minimization of the number of different cutting patterns used and the minimization of the maximum number of simultaneously open stacks. The first auxiliary objective arises in manufacturing environments where the adjustment of the cutting tools when changing the cutting patterns incurs increased costs and time spent in production. The second is crucial to face scenarios where the space near the cutting machine or the number of automatic unloading stations is limited. In this paper, we address the one-dimensional cutting stock problem, considering the additional goals of minimizing the number of different cutting patterns used and the maximum number of simultaneously open stacks. We propose two integer linear programming (ILP) formulations and a Constraint programming (CP) model for the problem. Moreover, we develop new upper bounds on the frequency of the cutting patterns in a solution and address some special cases in which the problem may be simplified. All three approaches are embedded into an iterative exact framework to find efficient solutions. We perform computational experiments using two sets of instances from the literature. The proposed approaches proved effective in determining the entire Pareto front for small problem instances, and several solutions for medium-sized instances with minimum trim loss, a reduced maximum number of simultaneously open stacks, and a small number of different used cutting patterns.

关键词： Cutting stock problem Open stacks Pattern sequencing Setup cost Mathematical formulation integer linear programming Constraint programming

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Supervisor Synthesis for Petri Nets With Uncontrollable and Unobservable Transitions

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年第2期21卷 1517-1525页

作者： Ran, Ning Li, Tingting Wang, Shouguang He, Zhou Hebei Univ Coll Elect & Informat Engn Lab Energy Saving Technol Baoding 071002 Peoples R China Zhejiang Gongshang Univ Coll Informat & Elect Engn Hangzhou 310018 Peoples R China Shaanxi Univ Sci & Technol Sch Elect & Control Engn Xian 710021 Peoples R China

This paper focuses on designing event feedback supervisors to enforce control specifications on Petri nets with uncontrollable and unobservable transitions. For each observation, the supervisor is able to select some controllable transitions to disable such that the system never reaches illegal markings. Two different methods are given to design such a supervisor. The first method computes the control policy by solving some integer linear programming problems, while the second one designs supervisors by taking advantage of the structural properties of a class of Petri nets. The computational efficiencies of these two methods increase successively at the expense of their application scopes. Two examples are given to illustrate the proposed methods, respectively.

关键词： Petri nets Monitoring Law Firing Computational efficiency Behavioral sciences integer linear programming Supervisory control linear constraints

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Integrating stop planning, timetabling and rolling stock planning on high-speed railway lines: A multi-objective optimization approach

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EXPERT SYSTEMS WITH APPLICATIONS 2024年第PartB期237卷

作者： Yang, Lin Li, Dewei Wang, Hui Gao, Yuan Beijing Inst Technol Sch Management & Econ Beijing 100081 Peoples R China Beijing Jiaotong Univ Dept Traff & Transportat Beijing 100044 Peoples R China Univ Hong Kong Dept Geog Hong Kong 999077 Peoples R China

Designing railway operational planning is a complex and challenging task to cope with fluctuating passenger demand and satisfy actual operational requirements. Focusing on high-speed railway (HSR) lines, this paper proposes an integrated modeling framework for phase-oriented railway operational planning. The framework simultaneously optimizes the stop planning, train timetable problem (TTP) and rolling stock planning (RSP). A multi-objective optimization model, with macro passenger demand, two train speed levels, and overtaking operations taken into account, is formulated to minimize the total train running distance, train dwell time, and rolling stock resources. The constraints involve the train operation zones, train operation process, passenger demand, rolling stock circulation conditions, and actual operational requirements. The proposed model is addressed using a framework based on the epsilon-constraint method, from which an approximate Pareto-optimal solution set is obtained. A case study on the Beijing-Shanghai HSR corridor demonstrates the effectiveness of the proposed approach and reveals some trade-offs between the proposed objectives.

关键词： High-speed railway Integrated railway operational planning integer linear programming Multi-objective optimization

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Cardinality Constraint Non-Uniform Sampling for Maximizing Reconstruction Accuracy of Time-Varying Signals

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IEEE TRANSACTIONS ON INFORMATION THEORY 2024年第9期70卷 6746-6756页

作者： Pandey, Sakshi Banerjee, Amit South Asian Univ Comp Sci Dept New Delhi 110068 India

Non-uniform sampling selects samples at irregular intervals for concise signal representation. Prior works on non-uniform sampling predominantly focused on maximizing reconstruction accuracy or optimizing sample size. However, a trade-off exists between the two factors, as increasing the sample size can improve the reconstruction accuracy, but it decreases the bandwidth efficiency. The reverse is true for under-sampling. Thus, it is important to balance the two factors. This motivates us to consider CAISOS, a CArdinalIty conStraint nOn-uniform Sampling problem that aims to select at most k sample points of a given time-varying signal such that the regenerated signal has the maximum reconstruction accuracy. Applications of CAISOS include fixed-rate sampling and signal compression in the time domain, such as in robotics and fixed-rate speech encoders. It proposes an integer linear programming model to address CAISOS and shows that the time complexity of the same increases exponentially with increasing signal size. It further proves that CAISOS is an NP-complete problem by showing that it is both NP and NP-hard by using a polynomial-time reduction from the 0/1 knapsack problem. Thus, the paper proposes a polynomial time heuristic based on the least-cost branch-and-bound approximation to solve CAISOS. Finally, it demonstrates the effectiveness of the proposed approaches through simulation by comparing them with the existing counterparts using various time-varying signals available in multiple databases.

关键词： Non-uniform sampling branch-and-bound optimization set cardinality integer linear programming NP-complete Non-uniform sampling branch-and-bound optimization set cardinality integer linear programming NP-complete

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Hierarchical Scheduling Mechanism Based on Relaxed Constraints for Complex Industrial Scenes

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第3期11卷 3237-3249页

作者： Nie, Tianzheng Yao, Haipeng Wang, Zunliang Guo, Jiawen Wang, Xiaolong Mai, Tianle Wu, Di Guo, Song Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Qilu Univ Technol Shandong Acad Sci Shandong Comp Sci Ctr Natl Supercomp Ctr JinanMinist EducKey Lab Comp Jinan 250316 Peoples R China Shandong Fundamental Res Ctr Comp Sci Shandong Prov Key Lab Comp Networks Jinan 250316 Peoples R China Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Hong Kong Polytech Univ Dept Comp Hung Hom Hong Kong Peoples R China

The rise of Time-Sensitive Networking (TSN) has sparked a significant transformation in the domain of industrial networks. Concurrently, industrial networks have established new benchmarks for communication quality, characterized by stringent requirements for low latency, minimal jitter, and enhanced reliability. In this context, the TSN subcommittee under the IEEE 802.1 working group has released a comprehensive collection of protocol standards. These standards are intricately crafted to ensure deterministic low latency in inherently unpredictable Ethernet environments. To enhance deterministic Quality of Service (QoS) in industrial networks and increase the flexibility of network scheduling paradigms, emerging technologies that combine TSN with Software-Defined Networking (TSSDN) have gained significant attention. Nevertheless, due to the complex and multifaceted nature of factory workflows and the varying scheduling requirements at different hierarchical levels, current industrial scheduling methods encounter challenges in efficiently managing network traffic in real-world factory environments. In this paper, we present a systematic framework designed for the scheduling of factory traffic. Additionally, we introduce two distinct scheduling mechanisms, each based on a framework with relaxed constraints. These mechanisms correspond to intra-level and inter-level traffic transmission in industrial networks. According to our experimental results, we observe an increase of 12.6% to 25.32% in the relaxed constraint scheduling mechanism when compared to the single scheduling scheme, along with a 9% reduction in the proportion of occupied queues.

关键词： Job shop scheduling Production facilities Switches Optimal scheduling Standards Software defined networking Jitter integer linear programming relaxed traffic scheduling constraints TSSDN

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