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21st IEEE International Symposium on Biomedical Imaging (ISBI)

作者： Woicik, Addie McCaw, Zachary R. Akle, Santiago Dulken, Benjamin Narayanan, Sanjana Probert, Christopher Insitro South San Francisco CA 94080 USA Univ Washington Paul G Allen Sch Comp Sci & Engn Seattle WA 98195 USA Stanford Sch Med Dept Pathol Stanford CA USA

ISBN: (纸本)9798350313345;9798350313338

Machine learning (ML) methods based on histopathology slides are increasingly used for cancer diagnosis and treatment. Analyses with specialized experimental stains, such as spatial proteomics, are often limited to tissue microarrays (TMAs) rather than whole slide images due to the cost of data generation. While different approaches for selecting tissue to include in a TMA exist, the impact of the sampling protocol on downstream ML-model performance is underexplored. Here, we present a general-purpose framework to evaluate ML performance of synthetic TMA datasets. We compare the performance of 16 synthetic TMA breast carcinoma datasets for predicting patient overall survival, immunohistochemistry subtype, and mutation status. We deduce several common design principles that are broadly applicable across TMA applications. Finally, we conduct a case study into principled and task-specific TMA sampling procedures in budget-constrained scenarios.

关键词： Tissue microarrays integer linear programming survival analysis IHC subtype mutation status

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Synthesis of Free-Labeled Petri Nets with Inhibitor Arcs 20

Synthesis of Free-Labeled Petri Nets with Inhibitor Arcs

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IEEE 20th International Conference on Automation Science and Engineering (CASE)

作者： Cheng, Wei Zhu, Lulai Matta, Andrea Politecn Milan Dept Mech Engn Via La Masa 1 I-20156 Milan Italy

ISBN: (纸本)9798350358513;9798350358520

This paper presents a method for synthesizing a free-labeled Petri net with inhibitor arcs (inhibitor net) from its generated finite language. Inhibitor arcs extend the modeling power of Petri nets to the Turing machine level, offering significant benefits for modeling physical systems such as parallel machine systems in manufacturing. However, inhibitor arcs modify the enabling conditions, complicating the synthesis problem and rendering previous methods inapplicable. To address this challenge, we introduce novel logical conditions to manage the altered enabling conditions and formulate the synthesis problem as an integer linear programming problem. Experimental results demonstrate the effectiveness of the proposed method.

关键词： integer linear programming

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Computer Classification of linear Codes Based on Lattice Point Enumeration 8th

Computer Classification of Linear Codes Based on Lattice Poi...

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8th International Conference on Mathematical Software (ICMS)

作者： Kurz, Sascha Friedrich Alexander Univ Erlangen Nuremberg Erlangen Germany Univ Bayreuth Bayreuth Germany

ISBN: (纸本)9783031645280;9783031645297

linear codes related to applications in Galois Geometry often require a certain divisibility of the occurring weights. In this paper we present an algorithmic framework for the classification of linear codes over finite fields with restricted sets of weights. The underlying algorithms are based on lattice point enumeration and integer linear programming. We present new enumeration and non-existence results for projective two-weight codes, divisible codes, and additive F-4-codes.

关键词： linear codes classification enumeration lattice point enumeration integer linear programming two-weight codes

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Representing Positive integers as a Sum of a Squarefree Number and a Small Prime 20th

Representing Positive Integers as a Sum of a Squarefree Numb...

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20th Combinatorial and Additive Number Theory, New York Number Theory Seminar, CANT 2022 and 21st Combinatorial and Additive Number Theory, New York Number Theory Seminar, CANT 2023

作者： Dalton, Jack Trifonov, Ognian Department of Mathematics University of South Carolina 1523 Greene Street ColumbiaSC29208 United States

We prove that every positive integer. n which is not equal to. 1, 2, 3, 6, 11, 30, 155, or 247 can be represented as a sum of a squarefree number and a prime not exceeding. √n. © The Author(s), under exclusive l... 详细信息

ISBN: (纸本)9783031650635

关键词： integer linear programming

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Novel Formulations and Improved Differential Evolution Algorithm for Optimal Lane Reservation With Task Merging

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第11期23卷 21329-21344页

作者： Wu, Peng Xu, Ling D'Ariano, Andrea Zhao, Yongxiang Chu, Chengbin Fuzhou Univ Sch Econ & Management Fuzhou 350108 Peoples R China Roma Tre Univ Dept Engn Rome Italy Univ Gustave Eiffel ESIEE Paris COSYS GRETTIA F-77454 Marnela La Vallee France

This paper investigates a new lane reservation problem with task merging that consists of optimally determining which lanes in a transportation network have to be reserved and designing reserved lane-based routes in the network for time-crucial transport tasks. Part of the tasks whose destinations are geographically close is merged to reduce the number of vehicles and transport costs. Reserved lanes can reduce the travel time of task vehicles passing through them, while they will generate negative impact on normal traffic, such as traffic delay to the vehicles on adjacent non-reserved lanes. The objective is to minimize the total negative impact of all reserved lanes. For this problem, two new integer linear programming (ILP) models are first developed. The complexity of the problem is proved to be NP-hard. Since commercial solver (like CPLEX) is time-consuming for solving it when the problem size increases, a fast and effective improved differential evolution algorithm (IDEA) is developed based on explored problem properties. Extensive experimental results for a real-life case and benchmark instances of up to 500 nodes in the network and 30 transport tasks show the favorable performance of the IDEA, as compared to CPLEX, differential evolution algorithm and genetic algorithm. Management insights are also drawn to support practical decision-making.

关键词： Task analysis Roads Transportation Merging Costs Games Uncertainty Lane reservation task merging integer linear programming differential evolution algorithm

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Revisiting Data Collection in Robotic Sensor Networks: A Budget-Constrained Traveling Salesman Perspective 21

Revisiting Data Collection in Robotic Sensor Networks: A Bud...

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21st IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS)

作者： Patil, Soham Chen, Yutian Tang, Bin Calif State Univ Dominguez Hills Dept Comp Sci Carson CA 90747 USA Calif State Univ Long Beach Econ Dept Long Beach CA 90840 USA

ISBN: (纸本)9798350363999;9798350364002

We focus on robotic sensor networks (RSNs), wherein mobile data collectors or robots are dispatched into the sensor field to collect data from the sensor nodes, and study a new algorithmic problem called battery-constrained data collection in RSNs (BC-DCR). Given an RSN of sensor nodes with varying numbers of sensory data packets to be collected and a robot with limited battery power, the goal of the BC-DCR is to dispatch the robot into the sensor field to collect the maximum number of data packets before it runs out of battery power and returns to the depot for recharging. Although extensive research has been conducted to achieve various performance objectives of data collection in RSNs, not much work has focused on the robot's limited battery power. It is critical to consider the robot's limited battery power to optimize the data-collecting performance of a large-scale RSN. We show that at the core of the BC-DCR is a new variation of the classic traveling salesman problem called the Budget-Constrained Traveling Salesman Problem (BC-TSP), which has not been adequately solved. We design an integer linear programming (ILP)-based optimal algorithm and a time-efficient iterative greedy algorithm to solve the BC-TSP. Via extensive simulations using real measurements of battery power and mobility models of robots, we show that a) our algorithms outperform the existing work by collecting 29.1% more packets with the same battery power of the robots and b) our BC-TSP-based approach achieves 32.02% more network lifetime of the RSN compared to the existing approach.

关键词： Data collection robotic sensor networks integer linear programming budget-constrained traveling salesman problem

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Emission-Based Relocation Strategies for Mobile Prefabrication Factories 1st

Emission-Based Relocation Strategies for Mobile Prefabricati...

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1st International Conference on Net-Zero Built Environment: Innovations in Materials, Structures, and Management Practices, NTZR 2024

作者： Ma, Jianxiang Revolti, Andrea Benedetti, Lorenzo Escamilla, Edwin Zea Habert, Guillaume ETH Zürich Zürich Switzerland Freie Universität Bozen Bolzano Italy EuroTube Foundation Dübendorf Switzerland

ISBN: (纸本)9783031696251

Complex linear infrastructure projects have a unique characteristic that the construction site moves as the project progresses, necessitating that off-site manufacturing should be mobile. A mobile prefabrication factory is a promising distributed production facility that meets such requirements and offers benefits such as carbon emissions reduction by shortening the distance between the construction site and the off-site prefabrication facility. However, factory relocations introduce significant variability in the distances for transporting materials to the factory and delivering the completed prefabricated elements from the factory to the construction site. This paper presents an integer linear programming model to identify a feasible relocation strategy that reduces the overall transportation carbon emissions. A case study of hyperloop construction, an ultra-high-speed vacuum ground transportation infrastructure, is conducted as a demonstration. The results show that using mobile prefabrication factories to supply linear infrastructure projects can significantly reduce the overall transportation carbon emissions by around 50% compared to the fixed factory scenario. The primary factor to optimize this problem is the total transportation distance of the prefabricated elements. Relocating the mobile factory four to six times aligns with achieving efficient performance in terms of reducing carbon emissions. This analysis offers insights into developing feasible factory relocation strategies for decision-makers in complex linear infrastructure projects. © The Author(s) 2025.

关键词： integer linear programming

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Greedy Approach for Optimizing Image View Layout on Various Sizes of 2D UI Container 4

Greedy Approach for Optimizing Image View Layout on Various ...

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4th International Conference on Electrical Engineering and Computer Science, ICECOS 2024

作者： Hiryanto, Lely Putra Wirawan, Andhika Tony Tarumanagara University Department of Informatics Engineering Jakarta Indonesia

ISBN: (纸本)9798350368253

One important feature of every augmentative and alternative communication (AAC) application is the image view layout (IVL) in a user interface (VI) container, whose size is bound by the device's screen size. The IVL problem deals with arranging a set of images in a two-dimensional UI container with a definitive size. The study seeks to maximize the use of the container space to fit in as many images as possible in such a way that the number of display sets for the overall images is minimum. We consider each image a picture card containing an image or a photograph and a text label with a fixed height but varying width. The IVL problem is a special case of the 2D Bin Packing Problem, which is NP Hard. To provide approximate solutions, we propose two greedy-based heuristic algorithms, which are Order-IVL and Best-Fit-IVL. For the experimental dataset, we use 148 picture cards obtained from an AAC application called VICARA. For 30% of the experimental scenarios, our evaluations show that Order-IVL produces one extra display set than Best-Fit-IVL. Furthermore, Best-Fit-IVL results in the same number of image display sets as the optimal solutions generated by solving the integer linear programming of the IVL problem. In addition, the Best-Fit-IVL consistently produces a tidy and neater arrangement of picture cards than Order-Ivlfor all experiment scenarios. © 2024 IEEE.

关键词： integer linear programming

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Fast Algorithms for Loop-Free Network Updates using linear programming and Local Search

Fast Algorithms for Loop-Free Network Updates using Linear P...

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IEEE Conference on Computer Communications (IEEE INFOCOM)

作者： Raecke, Harald Schmid, Stefan Vintan, Radu Tech Univ Munich Munich Germany TU Berlin Berlin Germany Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (纸本)9798350383515;9798350383508

To meet stringent performance requirements, communication networks are becoming increasingly programmable and flexible, supporting fast and frequent adjustments. However, reconfiguring networks in a dependable and transiently consistent manner is known to be algorithmically challenging. This paper revisits the fundamental problem of how to update the routes in a network in a (transiently) loop-free manner, considering both the Strong Loop-Freedom (SLF) and the Relaxed Loop-Freedom (RLF) property. We present two fast algorithms to solve the SLF and RLF problem variants exactly, to optimality. Our algorithms are based on a parameterized integer linear program which would be intractable to solve directly by a classic solver. Our main technical contribution is a lazy cycle breaking strategy which, by adding constraints lazily, improves performance dramatically, and outperforms the state-of-the-art exact algorithms by an order of magnitude on realistic medium-sized networks. We further explore approximate algorithms and show that while a relaxation approach is relatively slow, with a local search approach short update schedules can be found, outperforming the state-of-the-art heuristics. On the theoretical front, we also provide an approximation lower bound for the update time of the state-of-the-art algorithm in the literature. As a contribution to the research community, we made all our code and implementations publicly available.

关键词： integer linear programming

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Electric Vehicle Location Routing Problem With Vehicle Motion Dynamics-Based Energy Consumption and Recovery

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第8期23卷 10275-10286页

作者： Hulagu, Selin Celikoglu, Hilmi Berk Istanbul Tech Univ ITU ITU ITS Res Lab TR-34469 Istanbul Turkey Istanbul Tech Univ ITU Dept Civil Engn TR-34469 Istanbul Turkey

In this article we deal with the main critical issues of using electric vehicles in urban transport given the battery related limitations on driving range, and the network layout related limitations on the number of recharging stations. In this context, we seek the optimal routing plans together with the optimal locations of recharging stations for electric vehicle fleets through the Electric Vehicle Location Routing Problem with Intermediate Nodes (ELRP-IN) we propose. The ELRP-IN we formulate as a mathematical program considers the actual characteristics of battery discharging and recovering the braking energy. Energy consumption and recovery are determined through vehicle motion dynamics in conjunction with the 3-dimensional feature of the road geometry, passengers'/customers' demands on getting on and off, and the pre-defined speed profiles, where the graph corresponding to the road network is extended with the explicit consideration of intersections. By alternating the objectives adopted in the ELRP-IN formulation, we discuss through a number of numerical experiments involving real case instances the effects of both the objective functions and the parameters, including the consumption and the gain of energy, cost, traveled distance, and travel time, on the routing plans. Highlighting the finding that energy is not recovered in all the sections with descending grade, we reveal the direct effect of the elevation on the energy consumption, and hence on the location of a recharging station, where we discuss as well the limitation on energy recovery.

关键词： Routing Energy consumption Batteries Electric vehicles Roads Layout Resistance Road transportation electric vehicles energy consumption energy efficiency vehicle routing network theory (graphs) integer linear programming optimization

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