Academic literature on the topic 'Dynamic Truck Scheduling'

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Journal articles on the topic "Dynamic Truck Scheduling"

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Kim, Yongjin, Hani S. Mahmassani, and Patrick Jaillet. "Dynamic Truckload Truck Routing and Scheduling in Oversaturated Demand Situations." Transportation Research Record: Journal of the Transportation Research Board 1783, no. 1 (January 2002): 66–71. http://dx.doi.org/10.3141/1783-09.

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Kim, Jindae, and Changsoo Ok. "Distributed feedback control algorithm for dynamic truck loading scheduling problem." Applied Mathematics and Computation 199, no. 1 (May 2008): 275–84. http://dx.doi.org/10.1016/j.amc.2007.09.068.

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ZHANG, Ran, Zhuan WANG, and Yu-xin AN. "Research on Multi-objective Dynamic Task Scheduling of Cross-aisles Multi-layer Shuttle Truck Storage System Based on Elite Strategy." MATEC Web of Conferences 325 (2020): 05002. http://dx.doi.org/10.1051/matecconf/202032505002.

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In order to improve the operating efficiency of the cross-aisles shuttle truck system and the responsiveness to the disturbance of the return task, this paper first proposes a dynamic task scheduling process for the shuttle truck, using an event trigger mechanism. Each time a warehouse return task is generated, the corresponding scheduling optimization algorithm is triggered according to the current task combination mode to re-optimize the task sequence. Secondly, a task sequencing model is established under three combined task modes: full outbound / full return tasks, task mode with in-transit return tasks under the compound operation mode, task mode without in-transit return tasks under the compound operation mode. A fast non-dominated sorting genetic algorithm scheduling algorithm with elite strategy for compound operation mode is proposed. Finally, MATLAB was used to compile the simulation experiment system. The simulation analysis results show that the method can effectively improve the system’s operating efficiency, which verifies the feasibility and effectiveness of the scheduling method.
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Regnier-Coudert, Olivier, John McCall, Mayowa Ayodele, and Steven Anderson. "Truck and trailer scheduling in a real world, dynamic and heterogeneous context." Transportation Research Part E: Logistics and Transportation Review 93 (September 2016): 389–408. http://dx.doi.org/10.1016/j.tre.2016.06.010.

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Gerasimov, Yuri, and Anton Sokolov. "Decision Making Toolset for Woody Biomass Supply Chain in Karelia." Applied Mechanics and Materials 459 (October 2013): 319–24. http://dx.doi.org/10.4028/www.scientific.net/amm.459.319.

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The paper gives an overview of the models implemented in a new toolset for Russian logging companies. The toolset consists of a number of optimization tools, including the routing and scheduling of roundwood and energy wood harvesting teams, the sequencing of harvest areas, the estimation of available forest biomass potential in harvesting sites, and the planning of forest road networks. The optimization of routes is based on a two-phase algorithm where a heuristic optimization method is used to choose the best transportation paths and dynamic programming is used to choose the daily tasks and vehicle routing. The toolset has been tested in logging companies located in Russian Karelia. The results show that the toolset can be used to support a wide range of planning decisions at company level including truck routing, fleet utilization levels, and choice of transport method under new infrastructure assumptions.
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Gafarov, Evgeny, and Frank Werner. "Two-Machine Job-Shop Scheduling with Equal Processing Times on Each Machine." Mathematics 7, no. 3 (March 25, 2019): 301. http://dx.doi.org/10.3390/math7030301.

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In this paper, we consider a two-machine job-shop scheduling problem of minimizing total completion time subject to n jobs with two operations and equal processing times on each machine. This problem occurs e.g., as a single-track railway scheduling problem with three stations and constant travel times between any two adjacent stations. We present a polynomial dynamic programming algorithm of the complexity O ( n 5 ) and a heuristic procedure of the complexity O ( n 3 ) . This settles the complexity status of the problem under consideration which was open before and extends earlier work for the two-station single-track railway scheduling problem. We also present computational results of the comparison of both algorithms. For the 30,000 instances with up to 30 jobs considered, the average relative error of the heuristic is less than 1 % . In our tests, the practical running time of the dynamic programming algorithm was even bounded by O ( n 4 ) .
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Yan, Dong Mei. "Sensor Scheduling for WSN." Applied Mechanics and Materials 401-403 (September 2013): 2060–63. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.2060.

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In this paper, sensor scheduling algorithm tracking-oriented based on dynamic cluster and GDF is proposed. When the target run into the sensing filed of WSN, cluster is formed dynamically then Gaussian particle filter is used to predict the trajectory of target. With the target moving, some nodes are waked up to track the target and the others are allowed to sleep, so energy consumption is decreased remarkably.
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Brčić, Mario, and Danijel Mlinarić. "Tracking Predictive Gantt Chart for Proactive Rescheduling in Stochastic Resource Constrained Project Scheduling." Journal of information and organizational sciences 42, no. 2 (December 10, 2018): 179–92. http://dx.doi.org/10.31341/jios.42.2.2.

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Proactive-reactive scheduling is important in the situations where the project collaborators need to coordinate their efforts. The coordination is mostly achieved through the combination of the shared baseline schedule and the deviation penalties. In this paper, we present an extension of predictive Gantt chart to the proactive-reactive scheduling needs. It can be used to track the evolution of the relationship between dynamic and static elements through the time. The dynamic elements are evolving probability distributions due to the uncertainty and revealed information. The static elements are time-agreements in the baseline schedule. We demonstrate that in the state-of-the-art proactive-reactive scheduling, the baseline schedule is agnostic to the information received during the project execution. The sources of such inflexibility in the problem model and the scheduling methods are analyzed. The visualization is highlighted as a precursor to developing new methods that proactively change the baseline schedule in accordance with the gained information.
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Xu, Chen, Xueyan Xiong, Qianyi Du, Shudong Liu, Yipeng Li, Deliang Zhong, and Liu Yaqi. "Dynamic Scheduling Model of Rail-Guided Vehicle (RGV) Based on Genetic Algorithms in the Context of Mobile Computing." International Journal of Mobile Computing and Multimedia Communications 12, no. 1 (January 2021): 43–62. http://dx.doi.org/10.4018/ijmcmc.2021010103.

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Track guidance vehicle (RGV) is widely used in logistics warehousing and intelligent workshop, and its scheduling effectiveness will directly affect the production and operation efficiency of enterprises. In practical operation, central information system often lacks flexibility and timeliness. By contrast, mobile computing can balance the central information system and the distributed processing system, so that useful, accurate, and timely information can be provided to RGV. In order to optimize the RGV scheduling problem in uncertain environment, a genetic algorithm scheduling rule (GAM) using greedy algorithm as the genetic screening criterion is proposed in this paper. In the experiment, RGV scheduling of two-step processing in an intelligent workshop is selected as the research object. The experimental results show that the GAM model can carry out real-time dynamic programming, and the optimization efficiency is remarkable before a certain threshold.
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Harbering, Jonas, Abhiram Ranade, Marie Schmidt, and Oliver Sinnen. "Complexity, bounds and dynamic programming algorithms for single track train scheduling." Annals of Operations Research 273, no. 1-2 (October 7, 2017): 479–500. http://dx.doi.org/10.1007/s10479-017-2644-7.

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Dissertations / Theses on the topic "Dynamic Truck Scheduling"

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Sharma, Naveen, and n/a. "A multi agent system framework for.NET." University of Canberra. Information Sciences & Engineering, 2005. http://erl.canberra.edu.au./public/adt-AUC20060726.153250.

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This thesis presents an approach to modeling Multi Agent Systems (MAS). A framework and its implementation are presented as an extension to .NET. A number of definitions of agents are evaluated for the purpose of a broad understanding of the term software agent. Software agent has been defined in MAS context and its characteristics are identified and implemented. Motivation factors for building framework for MAS have been discussed. A number of existing technologies are discussed and evaluated. A number of agent systems previously developed are also being discussed in the middle part of the thesis. A model software agent has been defined and its characteristics are divided in two basic categories essential and optional. Its implementation has been distributed into different components throughout the MAS framework. Some of these characteristics are jointly implemented by a number of components and others responsibility rest on the individual components. Detail working of the MAS framework (i.e. what to do, when to do) is explained as guide to develop MAS using MAS framework. The protocols followed by the framework components to make communication possible between them are discussed at components level. The required information for developing MAS using MAS framework are also discussed. It answers the why, when and how questions in regards to using MAS framework A case study on Dynamic Truck Scheduling (DTS) system is discussed, designed and implemented using the MAS framework. DTS System has been used as a prototype application to test and evaluate the framework. DTS also represents a model problem that can be answered by using MAS; complete in-depth details about the problem statement are discussed. It also discusses the design and implementation of the solution along with the test results of the framework. Possible future expansion is presented in light of a number of limitations known of the MAS framework. The code working behind the different components of the MAS framework is given in appendices. Some important standards of XML that are used to pass information between agents and MAS framework components are also given in the format of tables.
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Book chapters on the topic "Dynamic Truck Scheduling"

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Icarte Ahumada, Gabriel, Jean Diaz Pinto, and Otthein Herzog. "A Dynamic Scheduling Multiagent System for Truck Dispatching in Open-Pit Mines." In Lecture Notes in Computer Science, 132–48. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71158-0_6.

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Conference papers on the topic "Dynamic Truck Scheduling"

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Zheng, Xiaojuan, Fan Shu, and Weijian Mi. "Research on genetic algorithm-based simulation of dynamic container truck scheduling." In 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE). IEEE, 2012. http://dx.doi.org/10.1109/csae.2012.6272743.

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Li, Guang-ru, and Sun Zhi. "Research on Dynamic Container Truck Scheduling Based on Energetic Algorithm and MAS." In 2010 International Conference on Artificial Intelligence and Computational Intelligence (AICI 2010). IEEE, 2010. http://dx.doi.org/10.1109/aici.2010.350.

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Zouhaier, Houda, and Lamjed Ben Said. "An Application Oriented Multi-Agent Based Approach to Dynamic Truck Scheduling at Cross-Dock." In 2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT). IEEE, 2016. http://dx.doi.org/10.1109/pdcat.2016.058.

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He, Chaozhe R., Wubing B. Qin, Necmiye Ozay, and Gábor Orosz. "Hybrid System Based Analytical Approach for Optimal Gear Shifting Schedule Design." In ASME 2015 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/dscc2015-9943.

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In this paper, we present a systematic design for gear shifting using a hybrid system approach. The longitudinal motion of the vehicle is regulated by a PI-controller that determines the required axle torque. The gear scheduling problem is modeled as a hybrid system and an optimization-based gear shifting strategy is introduced, which guarantees that the propulsion requirements are delivered while minimizing fuel consumption. The resulting dynamics is proved to be stable theoretically. In a case study, we compare our strategy with a standard approach used in the industry and demonstrate the advantages of our design for class 8 trucks.
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Zagorski, Scott B., Gary J. Heydinger, and Dennis A. Guenther. "Application of Linear Observers to Estimate States of a Roll Simulator." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-5889.

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In this research, a variety of Kalman Filters are implemented in an effort to estimate sled speed of a Roll Simulator. An Extended Kalman Filter (EKF) is incorporated to capture the nonlinear dynamics of the sled-platform assembly to estimate sled speed for the entire motion, as a linear Kalman Filter was found to be inadequate. When applied to experimental data, the EKF over-estimates sled speed, which is due to a disturbance force and/or uncertainty in system parameters. In combination with the disturbance observer, the Kalman Filter adequately estimates sled speed for experimental data. For lower speed/payload applications, a Kalman Filter using an accelerometer and measured drum speed is able to accurately track sled speed when a gain scheduling scheme is employed.
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Tasoujian, Shahin, Karolos Grigoriadis, and Matthew Franchek. "Delay-Dependent Output-Feedback Control for Blood Pressure Regulation Using LPV Techniques." In ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9098.

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Abstract This paper presents a delay-dependent parameter-varying control design approach to address the automated blood pressure regulation problem in the critical patient resuscitation using closed-loop administration of vasopressors. The mean arterial pressure (MAP) response of a patient subject to the intravenous vasoactive drug treatment is modeled as a linear parameter-varying (LPV) model, where varying model parameters and varying time-delay are considered as scheduling parameters of the system. Parameter-dependent Lyapunov-Krasovskii functionals are used to design an output-feedback dynamic controller to satisfy the closed-loop stability and reference MAP tracking requirements. The synthesis conditions are formulated in terms of Linear Matrix Inequalities (LMIs) that characterize the induced ℒ2-norm performance specification of the closed-loop system. The main objectives of the proposed control method in the presence of limitations posed by the time-varying model parameters and the large time-varying delay are to track the MAP reference command and maintain the blood pressure within the permissible range of commanded set-point, avoid undesirable overshoot and slow response, and to provide a smooth drug injection. Finally, to evaluate the performance of the proposed LPV blood pressure regulation approach, closed-loop simulations are conducted and the results confirm the effectiveness of the proposed control method against various simulated scenarios.
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Jaumard, Brigitte, Thai Hoa Le, Huaining Tian, Ali Akgunduz, and Peter Finnie. "An Enhanced Optimization Model for Scheduling Freight Trains." In 2013 Joint Rail Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/jrc2013-2465.

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We propose a new dynamic row/column management algorithm for the schedule of freight trains in a single/double track railway system. While many works have already been devoted to train scheduling, previously published optimization models all suffer from scalability issues. Moreover, very few of them consider the number of alternate tracks in the sidings for train meets, as well as the delay incurred by trains that take sidings. We propose a non time-indexed model, which takes into account such constraints, and we design a solution scheme with iterative additions/removals of constraints/variables in order to remain with a manageable sized mathematical program, while still ensuring convergence to an optimal solution. Numerical results are presented on data instances of Canada Pacific Railway. We evaluate the performance of the optimization model, and the sensitivity of the train schedules to the length of the operation hours, the length of the trains, and the departure times.
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Lewyta, Michael. "Commodity Movement Tracking (CMT): Bridging Operations and Commercial Transactions." In 2004 International Pipeline Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ipc2004-0312.

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It is crucial to accurately track the location of commodities transported on the Embridge Pipelines Inc. (EPI) liquids pipeline. Commercial scheduling is transformed to operational need and conversely, operation need to commerce. The Commodity Movement Tracking System (CMT) integrates the movement of product with business need, tracking inventories and linking products to commercial transactions across the pipeline. CMT tracks the batches within the pipeline and provides the ability to manage and reconcile system and tank inventories. Batches are tracked from initial receipt to final delivery, incorporating information from the SCADA system and the Pipeline Scheduling system. Daily schedules are published and recorded into the CMT system as events, based on volumetric information made available through the SCADA system. In the near future, receipt and delivery events will be electronically recorded into CMT from the field flow computers. Information is processed, producing results that reflect the positioning of each batch within the system, along with an estimated time of arrival at the next station. This process incorporates the challenges of side-streaming commodities, in and out of the lines, dynamic changing of the pipeline configurations, and changes in the pipeline diameter. The modeling process involves accurate re-positioning of the batches incorporating changes within the line configuration, static pipe diameter changes, and packing and draining of the line fill resulting from pressure changes. CMT is also responsible for inventory balancing within the EPI system. Comparing the various inputs and outputs from the system to the inventory on hand provides a quick accounting balance, not only on a system-wide basis, but also on a terminal-by-terminal and tank-by-tank basis. This paper discusses the modeling process, inputs and outputs of the integrated system and future direction of managing operational needs to enhance the soundness of commercial business transactions on EPI’s liquids pipeline system.
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