Bibliographies thématiques / Bi-level dynamic programming

Littérature scientifique sur le sujet « Bi-level dynamic programming »

Auteur : Grafiati
Publié le 25 mai 2024

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Articles de revues sur le sujet "Bi-level dynamic programming"

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Singh, Vishnu Pratap. « On Solving Linguistic Bi-Level Programming Problem Using Dynamic Programming ». International Journal of Fuzzy System Applications 10, no 1 (janvier 2021) : 43–63. http://dx.doi.org/10.4018/ijfsa.2021010103.

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In this work, a linguistic bi-level programming problem has been developed where the functional relationship linking decision variables and the objective functions of the leader and the follower are not utterly well known to us. Because of the uncertainty in practical life decision-making situation most of the time, it is inconvenient to find the veracious relationship between the objective functions of leader, follower, and the decision variables. It is expected that the source of information which gives some command about the objective functions of leader and follower is composed by a block of fuzzy if-then rules. In order to analyze the model, a dynamic programming approach with a suitable fuzzy reasoning scheme is applied to calculate the deterministic functional relationship linking the decision variables and the objective functions of the leader as well as the follower. Thus, a bi-level programming problem is constructed from the actual fuzzy rule-based to the conventional bi-level programming problem. A numerical example has been solved to signify the computational procedure.
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Lu, Ting, Zhongzhen Yang, Dongfang Ma et Sheng Jin. « Bi-Level Programming Model for Dynamic Reversible Lane Assignment ». IEEE Access 6 (2018) : 71592–601. http://dx.doi.org/10.1109/access.2018.2881290.

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ABO-SINNA, MAHMOUD A., et Azza H. Amer. « An Interactive Dynamic Fuzzy Goal Programming for Bi-level Multiobjective Linear Fractional Programming Problems. » JOURNAL OF ADVANCES IN MATHEMATICS 12, no 12 (28 février 2017) : 6991–7007. http://dx.doi.org/10.24297/jam.v12i12.3720.

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This paper presents an interactive dynamic fuzzy goal programming (DFGP) approach for solving bi-level multiobjective linear fractional programming (BL MOLFP) problems with the characteristics of dynamic programming (DP). In the proposed approach, the membership function of the objective goals of a problem with fuzzy aspiration levels are defined first as the membership function for vector of fuzzy goals of the decision variables controlled by first–level decision maker are developed first in the model formulation of the problem. The method of variable change, on the under and over deviational variables of the membership goals associated with the fuzzy goals of the model, is introduced to solve the problem efficiently by using linear goal programming (LGP) methodology. Then, under the framework of preemptive priority based GP, a multi stage DP model of the problem is used for achievement of the highest degree (unity) of each of the membership functions. In the decision process, the goal satisficing philosophy of GP is used recursively to arrive at the most satisfactory solution and the suggested algorithm to simplify the solution procedure by DP at each stage is proposed. This paper is considered as an extension work of Mahmoud A. Abo-Sinna and Ibrahim A. Baky (2010) by using dynamic approach. Finally, this approach is illustrated by a given numerical example.
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Yao, Liming, Zhongwen Xu, Mahdi Moudi et Zongmin Li. « Optimal water allocation in Iran : a dynamic bi-level programming model ». Water Supply 19, no 4 (27 septembre 2018) : 1120–28. http://dx.doi.org/10.2166/ws.2018.165.

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Abstract Water resource scarcity increases societal instability, poverty, and economic recession. Therefore, sound water resource management is vital to alleviating water crises in the agricultural, domestic, and industrial sectors. Southeast Iran, which currently lacks good water resource management, is experiencing a severe water crisis. Taking Zabol and Zahedan as examples, this paper seeks to optimize water allocation between the two cities using a dynamic bi-level programming model; the upper level objective minimizes the deviation between water demand and supply, and the lower level objective maximizes the net economic benefits in each sector. A sensitivity analysis is then conducted on the different sources of available water to provide more information on water allocation over time.
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Lin, Dung-Ying, Avinash Unnikrishnan et S. Waller. « A genetic algorithm for bi-level linear programming dynamic network design problem ». Transportation Letters 1, no 4 (octobre 2009) : 281–94. http://dx.doi.org/10.3328/tl.2009.01.04.281-294.

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Sun, Dazhi, Rahim F. Benekohal et S. Travis Waller. « Bi-level Programming Formulation and Heuristic Solution Approach for Dynamic Traffic Signal Optimization ». Computer-Aided Civil and Infrastructure Engineering 21, no 5 (juillet 2006) : 321–33. http://dx.doi.org/10.1111/j.1467-8667.2006.00439.x.

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Baozhuang, Niu. « A dynamic pricing model for postponement supply chain : the bi-level programming approach ». International Journal of Logistics Economics and Globalisation 1, no 3/4 (2008) : 383. http://dx.doi.org/10.1504/ijleg.2008.023169.

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Li, Minghua, Chengyong Xu, Yan Xu, Li Ma et Yun Wei. « Dynamic Sign Guidance Optimization for Crowd Evacuation considering Flow Equilibrium ». Journal of Advanced Transportation 2022 (21 janvier 2022) : 1–19. http://dx.doi.org/10.1155/2022/2555350.

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The dynamic exit sign has been verified as an effective means to guide the pedestrian during evacuation. The most critical mechanism with dynamic exit sign guidance is to balance the pedestrian flow on each exit route by optimizing the direction of signs. This paper formulates a bi-level programming model for the direction optimization problem of dynamic signs in buildings. In the bi-level program, the upper-level model is a system optimal model, aiming to minimize the total travel time by optimizing the dynamic sign direction. The lower-level model is a pedestrian assignment model satisfying the dynamic user optimal principle that describes the evacuee exit/route choice behaviour to achieve a balanced pedestrian distribution on the route. A method based on the fundamental diagram, the cell transmission model, and the point-queuing theory is developed to estimate evacuation travel time considering congestion and queuing. A heuristic algorithm is extended to solve the bi-level program. Finally, the proposed methodology is validated with numerical examples. Results reveal that the proposed model can produce the optimal dynamic sign direction, significantly improving the evacuation efficiency.
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Wong, Jui-Tsung, Chwen-Tzeng Su et Chun-Hsien Wang. « Stochastic dynamic lot-sizing problem using bi-level programming base on artificial intelligence techniques ». Applied Mathematical Modelling 36, no 5 (mai 2012) : 2003–16. http://dx.doi.org/10.1016/j.apm.2011.08.017.

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Soleimani-Alyar, Maryam, et Alireza Ghaffari-Hadigheh. « Dynamic Network Interdiction Problem with Uncertain Data ». International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, no 02 (avril 2018) : 327–42. http://dx.doi.org/10.1142/s0218488518500174.

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This paper proposes an uncertain multi-period bi-level network interdiction problem with uncertain arc capacities. It is proved that there exists an equivalence relationship between uncertain multi-period network interdiction problem and the obtained deterministic correspondent. Application of the generalized Benders’ decomposition algorithm is considered as the solution approach to the resulting mixed-integer nonlinear programming problem. Finally, a numerical example is presented to illustrate the model and the algorithm.
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Thèses sur le sujet "Bi-level dynamic programming"

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Guemri, Mouloud. « Heuristiques optimisées et robustes de résolution du problème de gestion d'énergie pour les véhicules électriques et hybrides ». Phd thesis, Institut National Polytechnique de Toulouse - INPT, 2013. http://tel.archives-ouvertes.fr/tel-00916394.

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Le système étudié durant cette thèse est un véhicule électrique hybride avec deux sources d'énergies (pile à combustible et supercondensateurs). L'objectif fixé est de minimiser la consommation du carburant tout en satisfaisant la demande instantanée en puissance sous des contraintes de puissance, de capacité et de stockage. Le problème a été modélisé sous la forme d'un problème d'optimisation globale. Nous avons développé de nouvelles méthodes heuristiques pour le résoudre et proposé le calcul d'une borne inférieure de consommation, en apportant de meilleurs résultats que ceux trouvés dans la littérature. En plus, une étude de robustesse a été réalisée afin de minimiser la consommation de pire-cas suite à une perturbation ou du fait d'incertitudes sur les données d'entrée, précisément sur la puissance demandée. Le but de cette étude est de prendre en compte les perturbations dès la construction des solutions afin d'éviter l'infaisabilité des solutions non robustes en situation perturbée. Les heuristiques de résolution du problème robuste modélisé sous la forme d'un problème de Minimax ont fourni des solutions moins sensibles aux perturbations que les solutions classiques.
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Abdel-Razzac, Amal. « Cooperation between LTE and emergent DVB technologies for an efficient delivery of mobile TV ». Electronic Thesis or Diss., Paris 6, 2015. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2015PA066036.pdf.

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La coopération entre les réseaux de diffusion classiques et les réseaux mobiles cellulaires pour une distribution commune de la télévision mobile est actuellement l'un des éléments clé discutés dans le cadre des nouvelles technologies de diffusion mobile; surtout l'extension mobile de la deuxième génération de diffusion de la télévision numérique terrestre (DVB-T2 Lite) et son suiveur le DVB-Next Generation Handheld (DVB-NGH).En fait, ces technologies de diffusion visent à coopérer avec la récente technologie de téléphonie mobile, connue sous le nom de Long Term Evolution (LTE) qui permet la diffusion de la TV Mobile grâce au protocole de diffusion des services multimédia dans les réseaux de téléphonie mobile (de nature unicast à priori) et connu sous le nom de enhanced-Multimedia Broadcast and Multicast Service feature (e-MBMS).Bien que la coopération entre les réseaux de diffusion DVB et ceux de téléphonie mobile n'est pas un nouveau sujet et a été étudiée avec l'introduction de la technologie de diffusion mobile précédente, connue sous le nom DVB-Handheld (DVB-H), la plupart des travaux traitants ce sujet ont considéré un scénario avec une zone de couverture commune entre le réseau de diffusion et celui cellulaire et ont évalué cette coopération en terme des gains de capacité apportés par DVB au réseau cellulaire et en terme d'amélioration de la fiabilité de transmission apportée par les réseaux cellulaire au DVB grâce à la possibilité des retransmissions unicast
The broadcast/cellular cooperation for a common delivery of Mobile TV is at the heart of the emerging mobile broadcast technologies, namely the mobile extension of the second generation digital video broadcasting for terrestrial reception (DVB-T2 Lite) and its follower DVB-Next Generation Handheld (DVB-NGH). These broadcast technologies aim to cooperate with the Long Term Evolution (LTE), as the latter is intended to be the bearer of Mobile TV thanks to its enhanced-Multimedia Broadcast and Multicast Service feature (e-MBMS). Even though the 3GPP/DVB cooperation is not a new topic and was investigated with the introduction of the previous DVB technology, known as DVB-Handheld (DVB-H), most of the works addressing this issue considered a common service area covered by both DVB and cellular systems and focused solely on the impact of such cooperation in terms of capacity gains brought by 3GPP and error repair gains brought by DVB. This strategy was judged to be expensive since a new and very dense DVB network was needed. In order to overcome this problem and decrease as much as possible the need for a new broadcast network, we propose in this thesis a hybrid DVB/LTE network with a coverage extension strategy, where the LTE system, planned for almost a universal coverage, is used to deliver Mobile TV in areas not covered by recent DVB-T2 Lite (or eventually DVB-NGH) network. In this context, we explore two main issues:1. Mobile TV services have to share LTE resources with other higher priority services such as voice traffic. The dynamicity of the latter will impact the Quality of Service (QoS) of Mobile TV. We propose a new QoS-based planning for the hybrid DVB/LTE so as to guarantee an acceptable watching experience without over-dimensioning the LTE system. We derive using Markov chain analysis and hitting time theory, several QoS metrics pertaining to mobile TV performance, such as interruption frequency and duration.2. A new business model which clarifies the relationships between the different actors of the ecosystem namely DVB and LTE operators as well as the TV channel providers and constructs the service area from an economic point of view is needed. In fact, the absence of a clear and viable economic model that resolves the monetary conflicts between cellular and broadcast operators was one of the main drawbacks behind the failure of the first attempt of mobile TV delivery by cooperating UMTS/DVB-H. We develop in this thesis a profit sharing strategy for the cooperative network, using coalition game concept Shapley value and Nash equilibrium for a self-enforcing strategy. We further develop a new framework using real option theory coupled with coalition games for investment decision in mobile TV networks (whether an operator should enter the mobile TV market and, if yes, when to do so) and show how operators can incorporate the uncertainties related to demand and network operation costs. We propose a bi-level dynamic programming algorithm to solve numerically the developed real option game
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Hsiao-Chi, Peng, et 彭曉琪. « Dynamic User Equilibrium Doubly Constrained Origin-Destination /Departure Time/ Route Choice Bi-level Programming Model ». Thesis, 2001. http://ndltd.ncl.edu.tw/handle/27838548984279748782.

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碩士
國立中央大學
土木工程研究所
89
Abstract This thesis, as follow-up study of Ying-Chun CHEN(1999), Tsung-Yi LEE(2000), attempts to further some important issues based on the dynamic user-equilibrium doubly constrained origin-destination /departure time/route choice model formulated using variational inequality approach and the solution algorithm of my model is using streamlined diagonalization lagrangian(GP) method to solves super network problem. As a result of road has link capacity constraint in the actual network, in order to my model conform to practicality condition, attempt to incorporate inflow link capacity constrained into it, and formulated the dynamic capacitated user-equilibrium doubly constrained origin-destination/departure time/route choice model. And numerical examples are provided for test and analysis. That uses bi-level programming method to formulate the dynamic signal timings control (DSTC) model. The upper level is dynamic signal timings optimal model, it tries to minimum the total travel cost by allocating the green times and determining link capacities, and the lower level is dynamic user-equilibrium doubly constrained origin-destination /departure time/route choice model, based on the fixed link capacities , searches the shortest travel time time-route for use. In accordance with variational inequality sensitivity analysis theory attain sensitivity analysis information by generalized inverse approach and developing solution algorithm. Finally, making several numerical examples to verify this research is correctly.
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Actes de conférences sur le sujet "Bi-level dynamic programming"

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Zhang, Shuai, Xinyi Zhang et Peng Wu. « Optimal dynamic bus lane reservation via bi-level programming ». Dans 2022 IEEE International Conference on Networking, Sensing and Control (ICNSC). IEEE, 2022. http://dx.doi.org/10.1109/icnsc55942.2022.10004089.

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Shouping, Gui, et Niu Baozhuang. « A Dynamic Pricing Model for Postponement Supply Chain : The Bi-level Programming Approach ». Dans 2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007). IEEE, 2007. http://dx.doi.org/10.1109/cisw.2007.4425566.

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Song, Guotao, Su Guo et Deyou Liu. « Bi-level programming method for integrated energy system considering thermal dynamic operation characteristics of pipelines and efficiency characteristics of devices ». Dans 2021 IEEE 4th International Electrical and Energy Conference (CIEEC). IEEE, 2021. http://dx.doi.org/10.1109/cieec50170.2021.9510830.

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Chen, Li, Huachao Dong et Zuomin Dong. « Integrated System Design and Control Optimization of Hybrid Electric Propulsion System Using a Bi-Level, Nested Approach ». Dans ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97456.

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Abstract Hybrid electric powertrain systems present as effective alternatives to traditional vehicle and marine propulsion means with improved fuel efficiency, as well as reduced greenhouse gas (GHG) emissions and air pollutants. In this study, a new integrated, model-based design and optimization method for hybrid electric propulsion system of a marine vessel (harbor tugboat) has been introduced. The sizes of key hybrid powertrain components, especially the Li-ion battery energy storage system (ESS), which can greatly affect the ship’s life-cycle cost (LCC), have been optimized using the fuel efficiency, emission and lifecycle cost model of the hybrid powertrain system. Moreover, the control strategies for the hybrid system, which is essential for achieving the minimum fuel consumption and extending battery life, are optimized. For a given powertrain architecture, the optimal design of a hybrid marine propulsion system involves two critical aspects: the optimal sizing of key powertrain components, and the optimal power control and energy management. In this work, a bi-level, nested optimization framework was proposed to address these two intricate problems jointly. The upper level optimization aims at component size optimization, while the lower level optimization carries out optimal operation control through dynamic programming (DP) to achieve the globally minimum fuel consumption and battery degradation for a given vessel load profile. The optimized Latin hypercube sampling (OLHS), Kriging and the widely used Expected Improvement (EI) online sampling criterion are used to carry out “small data” driven global optimization to solve this nested optimization problem. The obtained results showed significant reduction of the vessel LCC with the optimized hybrid electric powertrain system design and controls. Reduced engine size and operation time, as well as improved operation efficiency of the hybrid system also greatly decreased the GHG emissions compared to traditional mechanical propulsion.
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Febbo, Huckleberry, Tulga Ersal et Jeffrey L. Stein. « A Combined Plant/Controller Optimization Framework for Hybrid Vehicles With MPG, Emissions and Drivability Considerations ». Dans ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60335.

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The design and control of hybrid-electric vehicle (HEV) powertrains presents an optimization problem to balance the trade-off between multiple objectives, such as fuel economy, driv-ability, and emissions. However, current design methodologies do not simultaneously incorporate all of these three considerations into both the sizing and control layers of the optimization problem. This paper first demonstrates that the trade-offs between these objectives can be non-trivial in the HEV control problem. This motivates the need for a systematic design procedure that can take all three objectives into account. To address this need, the paper describes the development of a new and efficient design framework called the Hybrid-Vehicle Design Tool (HVDT), which adopts a bi-level optimization strategy. Efficiency is achieved by introducing a neural-network-based meta-model to predict the performance of the optimal control strategy obtained using Dynamic Programming (DP). To demonstrate the HVDT, a small HEV is designed for the UDDS and HWFET driving cycles separately. Results show that the optimized design can reduce fuel consumption, improve emissions and improve driv-ability when compared to the nominal design obtained using first principle design methodologies. Additionally, compared to using DP directly in the bi-level optimization, using the meta-model reduces the simulation from 238 to 16 days (93%) and from 132 to 16 days (88%) for the UDDS and HWFET cycles, respectively, with an acceptable compromise in the accuracy of predicting the performance of DP.
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Taaghi, Amirhossein, et Yongsoon Yoon. « Optimal Control Co-Design of a Parallel Electric-Hydraulic Hybrid Vehicle ». Dans WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2024. http://dx.doi.org/10.4271/2024-01-2154.

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<div class="section abstract"><div class="htmlview paragraph">This paper presents an optimal control co-design framework of a parallel electric-hydraulic hybrid powertrain specifically tailored for heavy-duty vehicles. A pure electric powertrain, comprising a rechargeable lithium-ion battery, a highly efficient electric motor, and a single or double-speed gearbox, has garnered significant attention in the automotive sector due to the increasing demand for clean and efficient mobility. However, the state-of-the-art has demonstrated limited capabilities and has struggled to meet the design requirements of heavy-duty vehicles with high power demands, such as a class 8 semi-trailer truck. This is especially evident in terms of a driving range on one battery charge, battery charging time, and load-carrying capacity. These challenges primarily stem from the low power density of lithium-ion batteries and the low energy conversion efficiency of electric motors at low speeds. To address these issues, a recent development is the electric-hydraulic hybrid powertrain. This system includes a hydro-pneumatic accumulator (i.e. a hydraulic energy storage system) and a hydraulic pump/motor (i.e. a hydraulic-mechanical energy conversion system) in addition to all the components of the electric powertrain. The high-level energy control methods of this hybrid powertrain have been extensively studied. In this work, an optimal control co-design framework involving hardware sizing and high-level energy control for a parallel electric-hydraulic hybrid powertrain is addressed. The objective is to maximize overall energy efficiency using a bi-level optimization method. The outer loop seeks optimal sizes for two energy storage systems: the rechargeable lithium-ion battery capacity and the hydro-pneumatic accumulator volume, determining the maximum electric and hydraulic storable energies. Meanwhile, the inner loop aims for optimal energy control with a set of energy storage system sizes using dynamic programming. Numerical studies demonstrate considerable benefits of the proposed control co-design method by applying it to real-world heavy-duty driving cycles. These benefits include reduced electric energy consumption of the lithium-ion battery, potentially allowing for a smaller battery size. Consequently, this increases load-carrying capacity and subjects the rechargeable battery to milder electric stress, thus extending the lifespan. These improvements are achieved through an aggressive use of hydraulic components during regenerative braking and high torque conditions at low vehicle speeds.</div></div>
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Rapports d'organisations sur le sujet "Bi-level dynamic programming"

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She, Ruifeng, et Yanfeng Ouyang. Generalized Link-Cost Function and Network Design for Dedicated Truck-Platoon Lanes to Improve Energy, Pavement Sustainability, and Traffic Efficiency. Illinois Center for Transportation, novembre 2021. http://dx.doi.org/10.36501/0197-9191/21-037.

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Recent development of autonomous and connected trucks (ACT) has provided the freight industry with the option of using truck platooning to improve fuel efficiency, traffic throughput, and safety. However, closely spaced and longitudinally aligned trucks impose frequent and concentrated loading on pavements, which often accelerates pavement deterioration and increases the life cycle costs for the highway agency. Also, effectiveness of truck platooning can be maximized only in dedicated lanes; and its benefits and costs need to be properly balanced between stakeholders. This paper proposes a network-design model to optimize (i) placement of dedicated truck-platoon lanes and toll price in a highway network, (ii) pooling and routing of ACT traffic from multiple origins and destinations to utilize these lanes, and (iii) configuration of truck platoons within these lanes (e.g., lateral displacements and vehicle separations). The problem is formulated as an integrated bi-level optimization model. The upper level makes decisions on converting existing highway lanes into dedicated platoon lanes, as well as setting user fees. The lower-level decisions are made by independent shippers regarding the choice of routes and use of platoon lanes vs. regular lanes; and they collectively determine truck traffic in all lanes. Link-cost functions for platoon lanes are obtained by simultaneously optimizing, through dynamic programming, pavement-rehabilitation activities and platoon configuration in the pavement's life cycle. A numerical case study is used to demonstrate the applicability and performance of the proposed model framework over the Illinois freeway system. It is shown that the freight traffic is effectively channelized on a few corridors of platoon lanes and, by setting proper user fees to cover pavement-rehabilitation costs, systemwide improvements for both freight shippers and highway agencies can be achieved.
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