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Updating origin-destination matrices and link probabilities in public transportation networks

PUBLIC TRANSPORT 2025年 1-27页

作者： Chavez-Hernandez, M. Victoria Rios-Solis, Yasmin a. Valencia, L. Hector Juarez Rios-Mercado, Roger Z. Inst Tecnol Autonomo Mexico Dept Matemat Rio Hondo 1 Mexico City Mexico Tecnol Monterrey Escuela Ingn & Ciencias Ave Eugenio Garza Sada 2501 Monterrey 64849 Nuevo Leon Mexico Univ Autonoma Metropolitana Dept Matemat Unidad Iztapalapa Ave San Rafael Atlixco 186 Mexico City 09340 Mexico Univ Autonoma Nuevo Leon Grad Program Elect Engn Ave Univ s-n San Nicolas De Los Garza 66455 NL Mexico

To update a public transportation origin-destination (OD) matrix, the link choice probabilities by which a user transits along the transit network are usually calculated beforehand. In this work, we reformulate the problem of updating OD matrices and simultaneously update the link proportions as an integer linear programming model based on partial knowledge of the transit segment flow along the network. We propose measuring the difference between the reference and the estimated OD matrices with linear demand deficits and excesses and simultaneously having slight deviations from the link probabilities to adjust to the observed flows in the network. In this manner, our integer linear programming model is more efficient in solving problems and is more accurate than quadratic or bilevel programming models. To validate our approach, we build an instance generator based on graphs that exhibit a property known as a "small-world phenomenon" and mimic real transit networks. We experimentally show the efficiency of our model by comparing it with an Augmented Lagrangian approach solved by a dual ascent and multipliers method. In addition, we compare our methodology with other instances in the literature.

关键词： Origin-destination matrix integer linear programming Transit counts Transit assignment problem

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What comes after optical-bypass network? A study on optical-computing-enabled network

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OPTICAL FIBER TECHNOLOGY 2024年 84卷

作者： Hai, Dao Thanh RMIT Univ Sch Sci Engn & Technol Ho Chi Minh City Vietnam

A new architectural paradigm, named, optical-computing-enabled network, is proposed as a potential evolution of the currently used optical-bypass framework. The main idea is to leverage the optical computing capabilities performed on transitional lightpaths at intermediate nodes and such proposal reverses the conventional wisdom in optical-bypass network, that is, separating in-transit lightpaths in avoidance of unwanted interference. In optical-computing-enabled network, the optical nodes are therefore upgraded from conventional functions of add-drop and cross-connect to include optical computing/processing capabilities. This is enabled by exploiting the superposition of in-transit lightpaths for computing purposes to achieve greater capacity efficiency. While traditional network design and planning algorithms have been well-developed for optical-bypass framework in which the routing and resource allocation is dedicated to each optical channel (lightpath), more complicated problems arise in optical-computing-enabled architecture as a consequence of intricate interaction between optical channels and hence resulting into the establishment of the so-called integrated/computed lightpaths. This necessitates for a different framework of network design and planning to maximize the impact of optical computing opportunities. In highlighting this critical point, a detailed case study exploiting the optical aggregation operation to re-design the optical core network is investigated in this paper. Optical aggregation enables the combination of lower-speed and/or lower-order format channels into a single higherrate and/or higher-order format one for saving spectrum resources and such new perspective give rises to major challenges involving aggregation assignments. Specifically, the determination of demands for aggregation, the nodes at which the optical aggregation takes place and the wavelength selection for aggregated lightpaths constitute a critical issue to be tackled. Nume

关键词： Optical-computing-enabled network Optical-computing-enabled networking In-network optical computing Optical-bypass network Computed lightpath Integrated lightpath Optical-layer intelligence Optical aggregation Routing Wavelength and aggregation assignment Optical network design and planning 2.0 integer linear programming

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Identification of labeled Petri nets from finite automata

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INFORMATION SCIENCES 2024年 667卷

作者： Zhu, Guanghui Yin, Li Li, Yaohui Li, Zhiwu Wu, Naiqi Xuchang Univ Sch Elect & Mech Engn Xuchang 461000 Peoples R China Macau Univ Sci & Technol Inst Syst Engn Taipa Macao Peoples R China

Automata and Petri nets are two typical models of discrete event systems. The paper studies the problem of converting a finite automaton into a Petri net that satisfies the specified structural features. More specifically, we identify a labeled Petri net from a nondeterminstic finite automaton such that the reachability graph of the identified net is isomorphic to the given automaton, meaning that the Petri net models exactly the same dynamic system as the automaton. The identified net necessarily satisfies the specified structural requirements, such as the numbers of places and transitions, absence of self -loops, the exact structure of a part of the net, and so on. Since label Petri nets and nondeterminstic finite automata are generalizations of Petri nets and deterministic finite automata, respectively, the proposed approach can identify a larger spectrum of Petri nets and effectively handle the nondeterminstic cases in the given automaton. Four kinds of conditions are first extracted from the given automaton, namely deterministic enabling conditions, nondeterministic enabling conditions (i.e., multiple transitions with the same label are enabled simultaneously at a marking), transition disabling conditions, and marking inequality conditions. Then, an integer linear programming problem is formulated by characterizing these four kinds of conditions using integer linear constraints. A labeled Petri net satisfying the structural requirements is obtained by solving the integer linear programming problem. We also present two examples to show the possible applications of the proposed identification approach.

关键词： Discrete event system Identification Synthesis Petri net Automaton integer linear programming

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Integrated Planning Model for Carbon Capture and Storage Systems Considering CO2 Pipeline Transportation Properties

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INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 2024年第43期63卷 18467-18478页

作者： Jiao, Yubo Wang, Wei Chen, Jie Li, Tao Sun, Wenyuan China Univ Petr Natl Engn Lab Pipeline Safety MOE Key Lab Petr Engn Beijing Key Lab Urban Oil & Gas Distribut Technol Beijing 102249 Peoples R China

Effective implementation of carbon capture and storage (CCS) hinges on the proper matching of the sources and sinks. In this study, we have investigated a mixed integer linear programming model for source-sink matching optimization considering hydrothermal properties of CO2 pipeline transportation. To incorporate the hydrothermal conditions into the optimization model, pressure and temperature control coefficients (K-P and K-T) are proposed and coupled. Subsequently, various operating conditions for transporting CO2 by pipeline are discussed with different combinations of pressure and temperature control coefficients, exploring the influence on the optimal source-sink matching. It is evident from the conclusions that the CO2 pipeline transportation constraints will inevitably affect optimal matching. However, considering CO2 dense phase transportation at the back-end of the supercritical CO2 pipeline transportation allows the transport temperature to drop below the critical temperature, which increases the number of effective matches, consequently increasing the amount of CO2 injected. For instance, when K-P = 1.1 and K-T = -0.15, the CO2 injection amount in the base planning region can be increased by 3.4%. It is important to implement a source-sink matching optimization analysis in combination with CO2 pipeline transportation conditions.

关键词： integer linear programming

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A rolling horizon for rolling stock maintenance scheduling problem with activities

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 196卷

作者： Folco, Pietro Sahli, Abderrahim Belmokhtar-Berraf, Sana Bouillaut, Laurent Univ Gustave Eiffel COSYS GRETTIA 16 Bd Newton F-77454 Champs Sur Marne France IKOS Lab 155 Rue Anatole France F-92300 Levallois Perret France

The rolling stock maintenance scheduling problem addressed here involves scheduling a set of cyclical preventive maintenance activities while considering resource capacity and geographically dispersed depots. The objective is to minimize both corrective and preventive maintenance costs using reliability features. We propose to use rolling horizon to decompose the problem into several successive subproblems such that each one tackles the scheduling of only the next cycle of activities instead of all cycles. The scheduled dates to be fixed should be as close as possible to their respective deadlines. Each train can have three status (in service, in maintenance, out of service). The activities deadlines are determined depending on component failure rate which has to be respected otherwise the train becomes out of service. An integer linear programming (ILP) model is proposed to solve the subproblem using a time oriented modeling to get an accurate maintenance cost (preventive and corrective) and respect a minimum of available trains. The rolling horizon allows to build a feasible schedule within a predefined planning horizon for moderate size problems with an interesting trade-off between computation time and solution quality.

关键词： Rolling stock Maintenance scheduling integer linear programming Rolling horizon

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Exact and heuristic solutions for the prize-collecting geometric enclosure problem

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2024年第4期31卷 2093-2122页

作者： Ramos, Natanael Cano, Rafael G. de Rezende, Pedro J. de Souza, Cid C. Univ Estadual Campinas Inst Comp Campinas Brazil

In the prize-collecting geometric enclosure problem (PCGEP), a set S of points in the plane is given, each with an associated benefit. The goal is to find a simple polygon P$\mathcal {P}$ with vertices in S that maximizes the sum of the benefits of the points of S enclosed by P$\mathcal {P}$ minus the perimeter of P$\mathcal {P}$ multiplied by a given nonnegative cost. The PCGEP is NP-complete and has applications to land surveying for exploration or preservation of natural resources. In this paper, we develop the first heuristic, called PCGEP-GR, for the PCGEP and revisit a previously proposed integer linear programming (ILP) model to solve it to optimality. We conducted a comprehensive experimental study of that heuristic and an exact algorithm based on the ILP model. We show that a new set of constraints, together with the previous set, is necessary to guarantee the correctness of the ILP model and introduce preprocessing strategies that allow us to prove optimality 40% faster on average. The proposed heuristic is able to reach the optimum in 32% of our benchmark instances and, for those with unknown optima, PCGEP-GR was found better than or at least as good solutions as the ones obtained by the cplex ILP solver in 54% of the cases. Notwithstanding these positive results, the design of effective heuristics for the PCGEP proved to be very challenging, which also led us to obtain a result that provides the theoretical foundation for future advances in the study of this problem.

关键词： optimal polygons fence enclosure computational geometry integer linear programming heuristics

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WORKER SCHEDULING OF BANBURY PROCESS USING GOAL programming: A TIRE MANUFACTURING COMPANY CASE STUDY

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2024年第2期31卷 258-277页

作者： Chaihanit, Chonnipa Butrat, Anan Supsomboon, Srisawat King Mongkuts Univ Technol North Bangkok KMUTNB Sirindhorn Int Thai German Grad Sch Engn TGGS Bangkok Thailand

In today's competitive business landscape, organizations must streamline their planning and management processes for efficiency and profitability. Effective resource management, especially in the case of human resources, is crucial. Scheduling challenges in human resource management become more complex when considering worker skills. Balancing fairness for workers and the company necessitates the inclusion of additional constraints and variables, making manual problem-solving more time-consuming and complex. This study proposes a Goal programming Method, a mathematical model that addresses both primary and goal constraints, to optimize solutions and minimize deviation variables. The case study of a real manufacturer's Banbury process department with 51 workers, 24 tasks, and two shifts has been analyzed. The mathematical model is utilized to allocate tasks, optimize worker skill utilization, and identify positions to close when worker availability falls short.

关键词： Worker Scheduling Shift Scheduling Goal programming Method Mathematical Model integer linear programming

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Optimizing Train Timetable Under Oversaturated Demand Conditions: A Variable-Splitting Lagrangian Approach for Big-M Constraints

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2024年第7期25卷 7265-7280页

作者： Tian, Xiaopeng Niu, Huimin Lanzhou Jiaotong Univ Sch Traff & Transportat Lanzhou 730070 Peoples R China

This study aims to optimize train timetables with hour-dependent origin-destination passenger demand for an oversaturated high-speed rail corridor, where some passengers may be delayed to the next hour. By introducing arc-based binary variables and assignment-based integer variables in the elaborated space-time network, we formulate the problem under consideration as an integer linear programming model with the objective of minimizing passenger travel time. To transform nonlinear demand loading constraints, multiple sets of big- $M$ constraints linking different types of variables are established equivalently. While relaxing these big- $M$ constraints under the standard Lagrangian decomposition framework, a thorny issue is that the lower bounds are often not ideal due to the existence of big- $M$ values. To tackle this important and common computational challenge, a novel approach is employed to split the arc-based variables into train skip-stopping and departing variables. Furthermore, a series of valid constraints are proposed to augment the decomposed assignment subproblem. With the help of Lagrangian dual information, a dynamic programming heuristic is also developed to generate feasible solutions to the primal problem. Finally, several numerical experiments are conducted to assess the efficiency and effectiveness of the proposed approach. The results show that compared with traditional solution approaches, the proposed approach can obtain satisfactory solutions in acceptable computation times for all the instances, in which the optimality gaps are less than 5% and the travel time is reduced by 17.28% on average.

关键词： Rail transportation Heuristic algorithms Schedules Rails integer linear programming Transportation Transforms Train timetabling oversaturated demand skip-stop scheduling variable-splitting Lagrangian relaxation

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SPTA 2.0: Enhanced Scalable Parallel Track Assignment Algorithm with Two-Stage Partition Considering Timing Delay

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ACM TRANSACTIONS ON DESIGN AUTOMATION OF ELECTRONIC SYSTEMS 2025年第2期30卷 1-23页

作者： Cai, Huayang Huang, Pengcheng Liu, Genggeng Huang, Xing Jing, Yidan Liu, Wenhao Wang, Ting-Chi Fuzhou Univ Fuzhou Fujian Peoples R China Northwestern Polytech Univ Xian Peoples R China Hsinchu NVIDIA Hsinchu Taiwan Natl Tsing Hua Univ Hsinchu Taiwan

Routability has always been a significant challenge in Very Large Scale Integration (VLSI) design. To overcome the potential mismatch between the global routing results and the detailed routing requirements, track assignment is introduced to achieve an efficient routability estimation. Moreover, with the increasing scale of circuits, the intricate interconnections among the components on the chip lead to increased timing delay in signal transmission, thereby significantly impacting the performance and reliability of the circuit. Thus, to further improve the routability of the circuit, it is also critical to realize an accurate estimation of the timing delay within the track assignment stage. Existing heuristic track assignment algorithms, however, are prone to local optimality, and thus fail to provide accurate routability estimations. In this article, we propose an enhanced scalable parallel track assignment algorithm called SPTA 2.0 for VLSI design, employing a two-stage partition strategy and considering timing delay. First, the proposed algorithm achieves efficient assignment of all wires by considering the routing information from both the global and local nets. Second, the overlap cost, the blockage cost, and the wirelength cost can be minimized to significantly improve the routability. Third, a critical wire controlling strategy is proposed to optimize signal timing delays inside nets. Finally, a two-stage partition strategy and a panel-subpanel-level parallelism are designed to further reduce the runtime, improving the scalability of the proposed methodology. Experimental results on multiple benchmarks demonstrate that the proposed method provides better routability estimations, and leads to superior track assignment solutions compared with existing algorithms.

关键词： integer linear programming track assignment very large scale integra-tion timing delay routability parallelism

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Approximate Counting of linear Extensions in Practice

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JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH 2024年 81卷 643-681页

作者： Talvitie, Topi Koivisto, Mikko Univ Helsinki Dept Comp Sci Helsinki Finland

We investigate the problem of computing the number of linear extensions of a given partial order on n elements. The problem has applications in numerous areas, such as sorting, planning, and learning graphical models. The problem is #P-hard but admits fully polynomial-time approximation schemes. However, the polynomial complexity bounds of the known schemes involve high degrees and large constant factors, rendering the schemes only feasible when n is some dozens. We present novel schemes, which stem from the idea of not requiring provable polynomial worst-case running time bounds. Using various new algorithmic techniques and implementation optimizations, we discover schemes that yield speedups by several orders of magnitude, enabling accurate approximations even when n is in several hundreds.

关键词： integer linear programming

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