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Modeling the spread of infectious diseases through influence maximization

OPTIMIZATION LETTERS 2022年第5期16卷 1563-1586页

作者： Yao, Shunyu Fan, Neng Hu, Jie Univ Arizona Dept Syst & Ind Engn Tucson AZ 85721 USA Wuhan Univ Sch Math & Stat Wuhan Hubei Peoples R China

Mathematical approaches, such as compartmental models and agent-based models, have been utilized for modeling the spread of the infectious diseases in the computational epidemiology. However, the role of social network structure for transmission of diseases is not explicitly considered in these models. In this paper, the influence maximization problem, considering the diseases starting at some initial nodes with the potential to maximize the spreading in a social network, is adapted to model the spreading process. This approach includes the analysis of network structure and the modeling of connections among individuals with probabilities to be infected. Additionally, individual behaviors that change along the time and eventually influence the spreading process are also included. These considerations are formulated by integer optimization models. Simulation results, based on the randomly generated networks and a local community network under the COVID-19, are performed to validate the effectiveness of the proposed models, and their relationships to the classic compartmental models.

关键词： Infectious diseases spread Influence maximization Optimization integer linear programming

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Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information

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INFORMS JOURNAL ON COMPUTING 2022年第1期34卷 227-242页

作者： Larsen, Eric Lachapelle, Sebastien Bengio, Yoshua Frejinger, Emma Lacoste-Julien, Simon Lodi, Andrea Univ Montreal Dept Comp Sci & Operat Res Montreal PQ H3T 1J4 Canada Univ Montreal CIRRELT Montreal PQ H3C 3J7 Canada Univ Montreal Mila Montreal PQ H2S 3H1 Canada Polytech Montreal CERC Montreal PQ H3T 1J4 Canada

This paper offers a methodological contribution at the intersection of machine learning and operations research. Namely, we propose a methodology to quickly predict expected tactical descriptions of operational solutions (TDOSs). The problem we address occurs in the context of two-stage stochastic programming, where the second stage is demanding computationally. We aim to predict at a high speed the expected TDOS associated with the second-stage problem, conditionally on the first-stage variables. This may be used in support of the solution to the overall two-stage problem by avoiding the online generation of multiple second-stage scenarios and solutions. We formulate the tactical prediction problem as a stochastic optimal prediction program, whose solution we approximate with supervised machine learning. The training data set consists of a large number of deterministic operational problems generated by controlled probabilistic sampling. The labels are computed based on solutions to these problems (solved independently and offline), employing appropriate aggregation and subselection methods to address uncertainty. Results on our motivating application on load planning for rail transportation show that deep learning models produce accurate predictions in very short computing time (milliseconds or less). The predictive accuracy is close to the lower bounds calculated based on sample average approximation of the stochastic prediction programs.

关键词： supervised learning deep learning integer linear programming stochastic programming

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An Electric Vehicle Routing Problem With Intermediate Nodes for Shuttle Fleets

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第2期23卷 1223-1235页

作者： Hulagu, Selin Celikoglu, Hilmi Berk Istanbul Tech Univ ITU IFS Res Lab TR-34469 Istanbul Turkey

In this article, we propose a variant of the electric vehicle routing problem considering explicitly the intermediate nodes. Ultimately aiming to provide an optimal routing plan for the shuttle fleet that serves to a university settlement internally, we consider a real road network by explicitly taking into account in the formulation the entire intersections existing and the time-varying passenger demand at shuttle stops, as well as the vehicle dynamics, battery, and recharging features. On purpose, a mathematical program to obtain the joint minimization of a number of objectives in terms of cost, i.e., vehicle operating, battery recharging, and recharging station purchasing, is formulated. Solutions employing an exact method are sought using models of mixed integer program within scenarios involving a number of features including the campus-wide passenger demand, seat capacity of shuttles, battery capacity of shuttles, and recharging station location. Further solutions to our model formulation have been obtained using a benchmark set of instances designed for a large-scale real network. Our findings show that considering a real road network as it is, is significant in exact routing solutions despite the fact that the level of network complexity is an issue. We suggest that a trade-off among the actuality of the network topology and the consequent computational load should be carefully made in order to obtain solutions using exact methods. As is shown, there is room to investigate further in details the dynamics of routing considering especially the effects of changes in flow conditions at intermediate nodes using our formulation.

关键词： Routing Roads Batteries Vehicle routing Vehicle dynamics Green products Electric vehicles vehicle routing network theory (graphs) integer linear programming optimization

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Ensuring Profit and QoS When Dynamically Embedding Delay-Constrained ICN and IP Slices for Content Delivery

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2022年第2期9卷 769-782页

作者： Rayani, Marsa Ebrahimzadeh, Amin Glitho, Roch H. Elbiaze, Halima Concordia Univ CIISE Montreal PQ H3G 2W1 Canada Univ Western Cape Comp Sci Programme ZA-7535 Cape Town South Africa Univ Quebec A Montreal UQAM Montreal PQ H2L 2C4 Canada

Content Delivery Networks (CDNs) are becoming more critical due to the tremendous growth of video traffic. This paper proposes a complete framework targeting the creation of Information Centric Network (ICN) and IP slices for content delivery. Leveraging ICN's in-network caching advantages, our solution is tailored to a VNF placement context where ICN and IP slices are dynamically created over a physical infrastructure. Embedding delay-constrained slices with high profits requires adjustments of the available resources based on the traffic and slice demands, which leads to the reassigning of the slices. However, slice reassignment may lead to additional costs, content disruption in service delivery, and QoS violation. We formulate the problem as an integer linear programming (ILP) and propose a cost-efficient dynamic network slicing heuristic. The objective is to maximize the profit of infrastructure providers while meeting the different QoS requirements of the slices. Our evaluation validates the effectiveness of profit maximization and analyzes the impact of QoS violation on infrastructure provider profit. The results are compared to a recent work from the literature and an optimal solution. The evaluation shows that our proposed heuristic is promising and offers a near-optimal solution while improving profitability and ensuring QoS.

关键词： Costs Content distribution networks Profitability Network slicing Information-centric networking Quality of service integer linear programming Content Delivery Networks (CDNs) Information Centric Networks (ICNs) Network slicing 5G

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Dealing with time in the multiple traveling salespersons problem with moving targets

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CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH 2022年第3期30卷 991-1017页

作者： Stieber, Anke Fuegenschuh, Armin Helmut Schmidt Univ Hamburg Germany Brandenburg Univ Technol Cottbus Senftenberg Cottbus Germany

The multiple traveling salespersons problem with moving targets is a generalization of the classical traveling salespersons problem, where the targets (nodes or objects) are moving over time. Additionally, for each target a visibility time window is given. The task is to find routes for several salespersons so that each target is reached exactly once within its visibility time window and the sum of all traveled distances of all salespersons is minimal. We present different modeling formulations for this TSP variant. The time requirements are modeled differently in each approach. Our goal is to examine what formulation is most suitable in terms of runtime to solve the multiple traveling salespersons problem with moving targets with exact methods. Computational experiments are carried out on randomly generated test instances to compare the different modeling approaches. The results for large-scale instances show, that the best way to model time requirements is to directly insert them into a formulation with discrete time steps.

关键词： Dynamic traveling salespersons problem Moving targets Time-relaxation integer linear programming Second-order cone programming

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Efficient management of industrial electric vehicles by means of static and dynamic wireless power transfer systems

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2022年第3-4期123卷 1249-1267页

作者： Faveto, Alberto Panza, Luigi Bruno, Giulia Cirimele, Vincenzo Furio, Saverio Stefano Lombardi, Franco Politecn Torino Dept Management & Prod Engn Corso Duca Abruzzi 24 I-10129 Turin Italy Univ Bologna Dept Elect Elect & Informat Engn Cesena Campus I-47521 Cesena Italy Enermove Srl Corso Castelfidardo 30-A I-10129 Turin Italy

Industrial companies are moving toward the electrification of equipment and processes, in line with the broader energy transition taking place across the economy. Particularly, the energy efficiency and, consequently, the reduction of environmental pollution of intralogistics activities have become a competitive element and are now an actual research and development objective. A wireless power transfer is a contactless electrical energy transmission technology based on the magnetic coupling between coils installable under the ground level and a coil mounted under the vehicle floor, and it represents an excellent solution to decrease the demand for batteries by reducing vehicle downtimes during the recharge. This work aims to define a methodology to determine the optimal positioning of wireless charging units across the warehouse, both for static and dynamic recharging. To this aim, firstly, a mathematical model of the warehouse is proposed to describe transfers and storage/retrieval operations executed by the forklifts. Then, an integer linear programming problem is applied to find the best possible layout of the charging infrastructures. The optimal solution respects the energetic requirements given by the customer and minimizes the overall system cost. The proposed approach was applied to optimize the installation in a real-size warehouse of a tire manufacturing company. Several scenarios were computer generated through discrete event simulation in order to test the optimizer in different warehouse conditions. The obtained results show that integrated dynamic and static WPT systems ensure a constant state of charge of the electric vehicles during their operations.

关键词： Electric vehicles Battery charging Wireless power transfer Green warehouse integer linear programming Discrete event simulation

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Method for Accelerating Unit Commitment Solution through Network Security Constraint Aggregation 6

Method for Accelerating Unit Commitment Solution through Net...

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6th International Conference on Power and Energy Technology, ICPET 2024

作者： Li, Linghao Cai, Zhi Hu, Xiaojing Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

ISBN: (纸本)9798350375855

This paper introduces a method for solving the unit commitment based on dimension reduction of security constraints. Initially, the security-constrained space of lines is obtained based on the transfer distribution factor matrix, and the similarity of line security constraints in the security-constrained space is measured by calculating the cosine of angle matrix. Then, based on the similarity and the similarity threshold, the security constraint similarity matrix of lines is obtained, and by applying the integer programming model to the similarity matrix to determine specific method of line aggregation, the security constraint set of aggregated lines is obtained. Subsequently, based on the above, a security-constrained unit commitment model suitable for line security constraint aggregation is developed, which effectively reduces the scale of security constraints and improves the solving efficiency of power system optimization. Finally, the proposed method is verified by numerical examples. © 2024 IEEE.

关键词： integer linear programming

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An Introduction to the Theory of linear integer Arithmetic 44

An Introduction to the Theory of Linear Integer Arithmetic

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44th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2024

作者： Chistikov, Dmitry Department of Computer Science University of Warwick United Kingdom

ISBN: (纸本)9783959773553

Presburger arithmetic, or linear integer arithmetic (LIA), is a logic that allows one to express linear constraints on integers: equalities, inequalities, and divisibility by nonzero n ∈ . More formally, it is the first-order theory of integers with addition and ordering. This paper offers a short introduction: what can be expressed in this logical theory, decision problems, and automated reasoning methods. We begin with an elementary introduction, explaining the language of linear arithmetic constraints by examples. We adopt a theoretical perspective, focusing on the decision problem: determining the truth value of a logical sentence. The following three views on Presburger arithmetic give us three effective methods for decision procedures: a view from geometry (using semi-linear sets), from automata theory (using finite automata and recognizable sets), and from symbolic computation (using quantifier elimination). The decision problem for existential formulas of Presburger arithmetic is essentially the feasibility problem of integer linear programming. By a fundamental result due to Borosh and Treybig [Proc. Am. Math. Soc. 55(2), 1976] and Papadimitriou [J. ACM 28(4), 1981], it belongs to the complexity class NP. Echoing the three views discussed above, we sketch three proofs of this result and discuss how these ideas have been used and developed in the recent research literature. This is a companion paper for a conference talk focused on the three views on Presburger arithmetic and their applications. The reader will require background knowledge at the level of undergraduate computer science curricula. The discussion of complexity aspects is more advanced. © 2024 Dmitry Chistikov.

关键词： integer linear programming

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Exact formulation and two-stage optimisation method for corridor allocation problem consider separated man-vehicle logistics passage in manufacturing workshops

Exact formulation and two-stage optimisation method for corr...

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作者： Ji, Dan Zhang, Zeqiang Liu, Junqi Zhao, Minjie Liang, Wei Liu, Silu School of Mechanical Engineering Southwest Jiaotong University Chengdu610031 China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province Chengdu610031 China Engineering Trainning Center Southwest Jiaotong University Chengdu610031 China

Passage is an essential logistics carrying structure in the layout, rational planning of its location can effectively improve production efficiency and safety of the workshop. In this paper, we introduce the concept of man-vehicle diversion and propose a novel corridor allocation problem with a separated man-vehicle logistics passage (CAP_SMVP). CAP_SMVP needs to sequence the facilities and determine the final exact location of the changeable sidewalk. Subsequently, we construct two mixed-integer linear programming models to minimise the material handling costs (MHC). The models for small-scale instances are solved precisely using GUROBI. We choose a two-stage method (combining meta-heuristic algorithm and linear programming, CMLP) to address large-scale problems. The correctness of the proposed model and CMLP is confirmed in solving the benchmark instances. Then, the calculation results of multiple algorithms for solving the initial CAP demonstrate the universality of the proposed algorithm. Finally, a real-world case is conducted, and managerial insights are provided. The comparison results show the proposed layout structure's advantages and highlight the efficiency of the two-stage method. © 2024 Elsevier Ltd

关键词： integer linear programming

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Automated Synthesis of Decision Lists for Polynomial Specifications over integers 25th

Automated Synthesis of Decision Lists for Polynomial Specifi...

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25th Conference on Logic for programming, Artificial Intelligence and Reasoning, LPAR 2024

作者： Akshay, S. Chakraborty, Supratik Goharshady, Amir Kafshdar Govind, R. Motwani, Harshit Jitendra Varanasi, Sai Teja IIT Bombay India HKUST Hong Kong Uppsala University Sweden

In this work, we consider two sets I and O of bounded integer variables, modeling the inputs and outputs of a program. Given a specification Post, which is a Boolean combination of linear or polynomial inequalities with real coefficients over I ∪ O, our goal is to synthesize the weakest possible pre-condition Pre and a program P satisfying the Hoare triple {Pre}P{Post}. We provide a novel, practical, sound and complete algorithm, inspired by Farkas’ Lemma and Handelman’s Theorem, that synthesizes both the program P and the pre-condition Pre over a bounded integral region. Our approach is exact and guaranteed to find the weakest pre-condition. Moreover, it always synthesizes both P and Pre as linear decision lists. Thus, our output consists of simple programs and preconditions that facilitate further static analysis. We also provide experimental results over benchmarks showcasing the real-world applicability of our approach and considerable performance gains over the state-of-the-art.1 © 2024, EasyChair. All rights reserved.

关键词： integer linear programming

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