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Optimal scheduling of shared autonomous electric vehicles with multi-agent reinforcement learning: A MAPPO-based approach

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NEUROCOMPUTING 2025年 622卷

作者： Tian, Jingjing Jia, Hongfei Wang, Guanfeng Huang, Qiuyang Wu, Ruiyi Gao, Heyao Liu, Chao Jilin Univ Coll Transportat Changchun 130022 Peoples R China

The advent of shared autonomous electric vehicles (SAEVs) is expected to decarbonize the transport sector and enable large-scale mobility on demand. Considering the highly dynamic nature of operation environments, it is appealing to investigate the optimal schedule decisions, comprising order-matching, relocation, and charge/ discharge with the V2G technology. Recent literature has investigated these schedule decisions with deep reinforcement learning (DRL) independently, neglecting the collaborative interactions among multiple autonomous vehicles. To this end, the fully dynamic schedule task is integrally described as a partially observable Markov decision process (POMDP) under the constraints of time-dependent demand, spatial-temporal varying electricity price, available vehicles and chargers. Then, we design a robust and extensible framework that combines multi-agent proximal policy optimization (MAPPO) and a binary linear programming (BLP) model to solve the optimization problem, in which SAEVs are regarded as agents to make decisions according to their local observations. Additionally, observation normalization and action masking are utilized to improve training efficiency. Numerical experiments are conducted with New York City yellow taxi data to simulate the real-time SAEV operating environment. These results demonstrate that the proposed MAPPO approach is expected to enhance the operators' revenue while improving the customer service rate compared to benchmark algorithms.

关键词： Shared autonomous electric vehicles Optimal scheduling Multi-agent proximal policy optimization binary linear programming

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Joint rolling stock rotation planning and depot deadhead scheduling in complicated urban rail transit lines

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2024年第2期314卷 665-684页

作者： Wang, Dian D'Ariano, Andrea Zhao, Jun Zhan, Shuguang Peng, Qiyuan Hefei Univ Technol Sch Automot & Transportat Engn Hefei 230009 Anhui Peoples R China Roma Tre Univ Dept Civil Comp Sci & Aeronaut Technol Engn I-00146 Rome Italy Southwest Jiaotong Univ Sch Transportat & Logist Chengdu 611756 Sichuan Peoples R China

This study investigates the joint rolling stock rotation planning and depot deadhead scheduling in complicated urban rail transit lines with multiple depots, multiple line services, and multiple compositions. The rotation planning aims at connecting the given train trips into train sequences (each of which is served by an individual rolling stock) and determining the routing plan of rolling stocks to pass through visited turnback stations while connecting train trips. The task of the depot deadhead scheduling is to determine conflict-free deadhead routes and deadhead timetables of rolling stocks between the origin/destination of each train sequence and corresponding depot. We formulate the studied problem as a generalized set partitioning-type model containing an exponential number of variables, by using a new time-space network representation and by proposing a novel modelling method for the departure-arrival headway requirement to control the number of constraints. Owing to the complexity of this model, a column generation-based algorithm is adopted to solve efficiently practical-size problems. We enhance a standard column generation (to compute tight lower bound) by further incorporating procedures of variable rounding and halted column generation, to strengthen the capability of searching for better quality solutions. Customized acceleration mechanisms are also explored to speed up the convergence of column generation and the computation of best-known integer solution. We compare our approach with three benchmark approaches and the trial-and-error-based empirical method used by rail dispatchers in practice. Computational results reveal that our approach outperforms these benchmark approaches by computing (near-)optimal solutions. Our optimized solution for a large real-world instance (computed within a practically reasonable computation time) is better than the empirical solution, in terms of all the considered objective function parts.

关键词： Transportation Rolling stock rotation planning Depot deadhead scheduling binary linear programming Column generation

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Design of Resilient Sensor Networks Balancing Resilience and Efficiency

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International Journal of Disaster Risk Science 2024年第1期15卷 107-115页

作者： Sergey N.Vecherin Kiril D.Ratmanski Luke Hogewood Igor Linkov Cold Regions Research and Engineering Laboratory Engineering Research and Development CenterHanoverNH 03755USA Environmental Laboratory Engineering Research and Development CenterVicksburgMS 39180USA

In recent years,the notion of resilience has been developed and applied in many technical areas,becoming exceptionally pertinent to disaster risk *** a disaster situation,accurate sensing information is the key to efficient recovery *** general,resilience aims to minimize the impact of disruptions to systems through the fast recovery of critical functionality,but resilient design may require redundancy and could increase *** this article,we describe a method based on binary linear programming for sensor network design balancing efficiency with *** application of the developed framework is demonstrated for the case of interior building surveillance utilizing infrared sensors in both twoand three-dimensional *** method provides optimal sensor placement,taking into account critical functionality and a desired level of resilience and considering sensor type and *** problem formulation,resilience requirements,and application of the optimization algorithm are described in *** of sensor locations with and without resilience requirements shows that resilient configuration requires redundancy in number of sensors and their intelligent *** tasks are successfully solved by the described method,which can be applied to strengthen the resilience of sensor networks by *** proposed methodology is suitable for large-scale optimization problems with many sensors and extensive coverage areas.

关键词： binary linear programming Optimal sensor placement Redundant networks Resilience and efciency Resilient sensor networks

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A quantum constraint generation framework for binary linear programs

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EPJ QUANTUM TECHNOLOGY 2025年第1期12卷 1-19页

作者： Czegel, Andras G.-Toth, Boglarka Univ Szeged Dept Computat Optimizat Arpad Ter 2 H-6720 Szeged Hungary

We propose a new approach to utilize quantum computers for binary linear programming (BLP), which can be extended to general integer linear programs (ILP). Quantum optimization algorithms, hybrid or quantum-only, are currently general purpose, standalone solvers for ILP. However, to consider them practically useful, we expect them to overperform the current state of the art classical solvers. That expectation is unfair to quantum algorithms: in classical ILP solvers, after many decades of evolution, many different algorithms work together as a robust machine to get the best result. This is the approach we would like to follow now with our quantum 'solver' solutions. In this study we wrap any suitable quantum optimization algorithm into a quantum informed classical constraint generation framework. First we relax our problem by dropping all constraints and encode it into an Ising Hamiltonian for the quantum optimization subroutine. Then, by sampling from the solution state of the subroutine, we obtain information about constraint violations in the initial problem, from which we decide which coupling terms we need to introduce to the Hamiltonian. The coupling terms correspond to the constraints of the initial binary linear program. Then we optimize over the new Hamiltonian again, until we reach a feasible solution, or other stopping conditions hold. Since one can decide how many constraints they add to the Hamiltonian in a single step, our algorithm is at least as efficient as the (hybrid) quantum optimization algorithm it wraps. We support our claim with results on small scale minimum cost exact cover problem instances.

关键词： Constraint generation Quantum optimization binary linear programming

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Toward Optimal Periodic Crowd Tracking via Unmanned Aerial Vehicle

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Computer Modeling in Engineering & Sciences 2023年第10期137卷 233-263页

作者： Khalil Chebil Skander Htiouech Mahdi Khemakhem Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlKharj11942Saudi Arabia Data Engineering and Semantics Research Unit Faculty of Sciences of SfaxUniversity of SfaxSfaxTunisia Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Mathematics and Business Intelligence College of Electronics and Telecommunications Engineering of SfaxUniversity of SfaxSfaxTunisia

Crowd management and analysis(CMA)systems have gained a lot of interest in the vulgarization of unmanned aerial vehicles(UAVs)*** tracking using UAVs is among the most important services provided by a *** this paper,we studied the periodic crowd-tracking(PCT)*** consists in usingUAVs to follow-up crowds,during the life-cycle of an open crowded area(OCA).Two criteria were considered for this *** first is related to the CMA initial investment,while the second is to guarantee the quality of service(QoS).The existing works focus on very specified assumptions that are highly committed to CMAs applications *** study outlined a new binary linear programming(BLP)model to optimally solve the PCT motivated by a real-world application study taking into consideration the high level of *** closely approach different real-world contexts,we carefully defined and investigated a set of parameters related to the OCA characteristics,behaviors,and theCMAinitial infrastructure investment(e.g.,UAVs,charging stations(CSs)).In order to periodically update theUAVs/crowds andUAVs/CSs assignments,the proposed BLP was integrated into a linear algorithm called PCTs *** main objective was to study the PCT problem fromboth theoretical and numerical *** prove the PCTs solver effectiveness,we generated a diversified set of PCTs instances with different scenarios for simulation *** empirical results analysis enabled us to validate the BLPmodel and the PCTs solver,and to point out a set of new challenges for future research directions.

关键词： Unmanned aerial vehicles periodic crowd-tracking problem open crowded area optimization binary linear programming crowd management and analysis system

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Image super resolution via combination of two dimensional quaternion valued singular spectrum analysis based denoising, empirical mode decomposition based denoising and discrete cosine transform based denoising methods

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MULTIMEDIA TOOLS AND APPLICATIONS 2023年第15期82卷 22705-22722页

作者： Cheng, Yingdan Ling, Bingo Wing-Kuen Lin, Yuxin Huang, Ziyin Chan, Yui-Lam Guangdong Univ Technol Fac Informat Engn Guangzhou 510006 Peoples R China Hong Kong Polytech Univ Dept Elect & Informat Engn Hung Hom Hong Kong Peoples R China

This paper formulates the image super resolution problem as various denoising problems. In particular, the discrete cosine transform zero padding approach is used to generate an initial high resolution image. Then, three different time frequency analysis based denoising methods are applied iteratively to improve the quality of the super resolution image. In particular, the two dimensional quaternion valued singular spectrum analysis (2DQSSA) based denoising method, the empirical mode decomposition (EMD) based denoising method and the discrete cosine transform based denoised method are applied. For the 2DQSSA based denoising method, the luminance plane is used as the real part of the quaternion valued image. Since different color planes in the quaternion valued image are fused together via the quaternion valued operation, some high frequency information missing in one color plane can be generated using those in other color planes. On the other hand, for the EMD based denoising method, the selection of the intrinsic mode functions (IMFs) is formulated as a binary linear programming problem. Here, the high frequency components generated by the aliasing are removed by discarding some IMFs. The computer numerical simulation results show that our proposed method can achieve the super resolution performance better than those without performing any one of the above three time frequency analysis based denoising.

关键词： Super resolution image Two dimensional quaternion valued singular spectrum analysis Empirical mode decomposition Discrete cosine transform binary linear programming

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Placement of SDN controllers based on network setup cost and latency of control packets

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COMPUTER COMMUNICATIONS 2023年第1期208卷 15-28页

作者： Naseri, Abdullah Ahmadi, Mahmood PourKarimi, Latif Razi Univ Comp Engn & Informat Technol Dept Kermanshah Iran Razi Univ Dept Math Kermanshah Iran

Software-defined networking (SDN) was developed to simplify the management of computer networks. In the SDN architecture, the control layer is completely decoupled from the data layer. Moreover, network software configuration is also possible. To setup an SDN, you need a device called controller, which is not available in traditional networks. In the control layer, there are several controllers that control the data layer switches. The type, number and place of these controllers directly affect the cost and average latency of control packets. Since achieving the lowest setup cost and the minimum latency of the control packets (between switches and controllers, and among controllers) is of great importance at the same time, in this paper, a binary linear programming model is proposed to achieve the trade-off between them in wide area networks(WAN). The model determines the type, place and minimum number of required controllers by receiving the place of the switches, the amount of processing capacity of the controllers and the setup cost of each controller. Accordingly, it reduces the setup cost, average latency between switches and controllers as well as average latency among controllers in comparison with previous methods. The results of the study show that the model has the lowest setup cost and the minimum average latency of control packets (switch-to-controller and controller-to-controller) in controllers placement compared to the previous methods.

关键词： SDN-WAN SDN controller Controller placement problem Latency binary linear programming

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Outsourcing Optimization in Footwear Industry: The Case of a Portuguese Company 32nd

Outsourcing Optimization in Footwear Industry: The Case of a...

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32nd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Costa e Silva, Eliana Francisco, Raquel Sousa, Sandra P. Braga, Vitor Politecn Porto CIICESI ESTG Felgueiras Portugal Univ Minho NIPE Braga Portugal Politecn Porto ESTG Felgueiras Portugal

ISBN: (纸本)9783031382406;9783031382413

When market's demand exceeds the company's manufacturing capacity, subcontracting is generally considered an effective alternative. This work presents an empirical study with real data from a Portuguese company in the footwear industry. The aim is to propose an approach, based on mathematical programming, to support production planning decision-making. More precisely, it is expected to contribute to a working tool that can assist the company in planning the distribution of orders for internal or external production, while minimizing the total production costs. The results point to benefits in reducing the number of orders to produce externally. Further, no relevant differences were found for biweekly and monthly, and by article and by order planning.

关键词： Outsourcing Footwear Industry Optimization binary linear programming Assignment Problem

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Resilience in distributed sensor networks 33

Resilience in distributed sensor networks

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Conference on Infrared Imaging Systems - Design, Analysis, Modeling, and Testing XXXIII Part of SPIE Defense and Commercial Sensing Conference

作者： Ratmanski, Kiril Vecherin, Sergey US Army Corps Engineers Engn Res & Dev Ctr 3909 Halls Ferry Rd Vicksburg MS 39180 USA

ISBN: (纸本)9781510650893;9781510650886

With the advent of cheap and available sensors, there is a need for intelligent sensor selection and placement for various purposes. While previous research was focused on the most efficient sensor networks, we present a new mathematical framework for efficient and resilient sensor network installation. Specifically, in this work we formulate and solve a sensor selection and placement problem when network resilience is also a factor in the optimization problem. Our approach is based on the binary linear programming problem. The generic formulation is probabilistic and applicable to any sensor types, line-of-site and non-line-of-site, and any sensor modality. It also incorporates several realistic constraints including finite sensor supply, cost, energy consumption, as well as specified redundancy in coverage areas that require resilience. While the exact solution is computationally prohibitive, we present a fast algorithm that produces a near-optimal solution that can be used in practice. We show how such formulation works on 2D examples, applied to infrared (IR) sensor networks designed to detect and track human presence and movements in a specified coverage area. Analysis of coverage and comparison of sensor placement with and without resilience considerations is also performed.

关键词： resilient networks optimal sensor placement redundant networks binary linear programming probabilistic framework

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Precise Worst-Case Blocking Time of Tasks Under Priority Inheritance Protocol

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IEEE TRANSACTIONS ON COMPUTERS 2021年第11期70卷 1901-1913页

作者： Faldella, Eugenio Loreti, Daniela Univ Bologna Dept Comp Sci & Engn I-40126 Bologna Italy

The problem of precisely computing the worst-case blocking time that tasks may experience is one of the fundamental issues of schedulability analysis of real-time applications. While exact methods have been proposed for more sophisticated protocols, the problem is indeed complex in case of the Priority Inheritance Protocol, even restricting the attention to uniprocessor systems, non-nested resource accesses, and non-self-suspending tasks. Besides a very simple method leading in general to loose upper bounds, only one algorithm of exponential complexity has been so far reported in literature to tighten such bounds. In this article, we describe a novel approach which, leveraging an operational research technique for modeling the problem, computes the same tight bounds in polynomial time. We then discuss the scenarios in which, assuming no conditional statements in the tasks' code, the computed bounds derive from an actually impossible blocking chain, and we refine the initial model to more precisely compute the worst-case blocking times for any task set in any possible operating condition.

关键词： Task analysis Protocols Real-time systems Upper bound Computational modeling Complexity theory linear programming Hard real-time multitasking applications exclusive access resources basic priority inheritance protocol binary linear programming

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