Relevant bibliographies by topics / Bilevel optimal control

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Bilevel optimal control'

Author: Grafiati
Published: 23 November 2024

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Journal articles on the topic "Bilevel optimal control"

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Mehlitz, Patrick, and Gerd Wachsmuth. "Weak and strong stationarity in generalized bilevel programming and bilevel optimal control." Optimization 65, no. 5 (December 31, 2015): 907–35. http://dx.doi.org/10.1080/02331934.2015.1122007.

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Ye, Jane J. "Optimal Strategies For Bilevel Dynamic Problems." SIAM Journal on Control and Optimization 35, no. 2 (March 1997): 512–31. http://dx.doi.org/10.1137/s0363012993256150.

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Bonnel, Henri, and Jacqueline Morgan. "Semivectorial Bilevel Convex Optimal Control Problems: Existence Results." SIAM Journal on Control and Optimization 50, no. 6 (January 2012): 3224–41. http://dx.doi.org/10.1137/100795450.

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Dempe, S. "Computing optimal incentives via bilevel programming." Optimization 33, no. 1 (January 1995): 29–42. http://dx.doi.org/10.1080/02331939508844061.

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Ye, Jianxiong, and An Li. "Necessary optimality conditions for nonautonomous optimal control problems and its applications to bilevel optimal control." Journal of Industrial & Management Optimization 13, no. 5 (2017): 1–21. http://dx.doi.org/10.3934/jimo.2018101.

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Lin, Hongzhi. "Optimal Design of Cordon Sanitaire for Regular Epidemic Control." Advances in Civil Engineering 2021 (June 1, 2021): 1–11. http://dx.doi.org/10.1155/2021/5581758.

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The outbreak of COVID-19 has disrupted our regular life. Many state and local authorities have enforced a cordon sanitaire for the protection of sensitive areas. Travelers can only travel across the cordon after being qualified. This paper aims to propose a method to determine the optimal deployment of cordon sanitaire in terms of the number of parallel checkpoints at each entry link for regular epidemic control. A bilevel programming model is formulated where the lower-level is the transport system equilibrium with queueing to predict traffic inflow, and the upper-level is queueing network optimization, which is an integer nonlinear programming. The objective of this optimization is to minimize the total operation cost of checkpoints with a predetermined maximum waiting time. Note that stochastic queueing theory is used to represent the waiting phenomenon at each entry link. A heuristic algorithm is designed to solve the proposed bilevel model where the method of successive averages (MSA) is adopted for the lower-level model, and the genetic algorithm (GA) is adopted for the upper-level model. An experimental study is conducted to demonstrate the effectiveness of the proposed method and algorithm. The results show that the methods can find a good heuristic optimal solution. These methods are useful for policymakers to determine the optimal deployment of cordon sanitaire for hazard prevention and control.
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Atiya Wardil *, Othman, and Samera Khaleel Ibrahim. "The Bi-level Programming Approach to Improve the Inventory Control System with a Practical Application." Journal of Economics and Administrative Sciences 30, no. 142 (September 6, 2024): 509–31. http://dx.doi.org/10.33095/gd8dy062.

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In this research, we investigated addressing the challenges associated with the seasonal allergic medical drug inventory system. The focus was on determining the optimal demand by calculating the Economic Order Quantity (EOQ) and achieving the lowest cost within the Pharmaceutical Industries and Medical Supplies company in Samarra. The primary objective was to efficiently meet the demand for seasonal allergy medications by identifying the optimal demand for medical drugs. The study encompassed two types of seasonal allergy medications, namely Samatifen drink and VALIAPAM 2 pills. The calculation of the lowest cost involved two methods: the multi-component production model without deficit, with restrictions, the solution was done using the classical method (normal) and mathematical analyses, utilizing tools such as QM and Win Qsb. Additionally, linear quadratic bilevel programming (LQBP) was employed. The LQBP model comprised an upper-level decision maker (leader) and a lower-level decision maker (follower). The transformation of the bilevel model into a single-level model was accomplished through the application of Karush-Kuhn-Tucker (KKT) conditions, and the solution was obtained using the modified simplex algorithm. The study's findings underscore the effectiveness of the LQBP method in identifying the optimal solution for the inventory problem by calculating the lowest cost. This approach significantly reduced medical drug inventory-related costs, with a value of 1,496,700,000 Iraqi Dinars (ID) and a production of 1200,700 ID. Notably, this cost was considerably lower than the total cost value obtained using the classical method, which was 1,719,166 ID/year, with a production of 2526,1773 ID. Therefore, bilevel programming (BLPP) demonstrates superior efficiency, providing more accurate and cost-effective solutions. This research emphasizes the potential of bilevel programming in optimizing medical drug inventory systems and contributes to the advancement of operational research in the healthcare sector. Paper type: Research Paper
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Amouzegar, Mahyar A., and Khosrow Moshirvaziri. "Determining optimal pollution control policies: An application of bilevel programming." European Journal of Operational Research 119, no. 1 (November 1999): 100–120. http://dx.doi.org/10.1016/s0377-2217(98)00336-1.

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Knauer, Matthias. "Fast and save container cranes as bilevel optimal control problems." Mathematical and Computer Modelling of Dynamical Systems 18, no. 4 (August 2012): 465–86. http://dx.doi.org/10.1080/13873954.2011.642388.

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Chen, Yi, Kadhim Hayawi, Meikai Fan, Shih Yu Chang, Jie Tang, Ling Yang, Rui Zhao, Zhongqi Mao, and Hong Wen. "A Bilevel Optimization Model Based on Edge Computing for Microgrid." Sensors 22, no. 20 (October 11, 2022): 7710. http://dx.doi.org/10.3390/s22207710.

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With the continuous progress of renewable energy technology and the large-scale construction of microgrids, the architecture of power systems is becoming increasingly complex and huge. In order to achieve efficient and low-delay data processing and meet the needs of smart grid users, emerging smart energy systems are often deployed at the edge of the power grid, and edge computing modules are integrated into the microgrids system, so as to realize the cost-optimal control decision of the microgrids under the condition of load balancing. Therefore, this paper presents a bilevel optimization control model, which is divided into an upper-level optimal control module and a lower-level optimal control module. The purpose of the two-layer optimization modules is to optimize the cost of the power distribution of microgrids. The function of the upper-level optimal control module is to set decision variables for the lower-level module, while the function of the lower-level module is to find the optimal solution by mathematical methods on the basis of the upper-level and then feed back the optimal solution to the upper-layer. The upper-level and lower-level modules affect system decisions together. Finally, the feasibility of the bilevel optimization model is demonstrated by experiments.
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Dissertations / Theses on the topic "Bilevel optimal control"

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Mehlitz, Patrick. "Contributions to complementarity and bilevel programming in Banach spaces." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2017. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-227091.

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In this thesis, we derive necessary optimality conditions for bilevel programming problems (BPPs for short) in Banach spaces. This rather abstract setting reflects our desire to characterize the local optimal solutions of hierarchical optimization problems in function spaces arising from several applications. Since our considerations are based on the tools of variational analysis introduced by Boris Mordukhovich, we study related properties of pointwise defined sets in function spaces. The presence of sequential normal compactness for such sets in Lebesgue and Sobolev spaces as well as the variational geometry of decomposable sets in Lebesgue spaces is discussed. Afterwards, we investigate mathematical problems with complementarity constraints (MPCCs for short) in Banach spaces which are closely related to BPPs. We introduce reasonable stationarity concepts and constraint qualifications which can be used to handle MPCCs. The relations between the mentioned stationarity notions are studied in the setting where the underlying complementarity cone is polyhedric. The results are applied to the situations where the complementarity cone equals the nonnegative cone in a Lebesgue space or is polyhedral. Next, we use the three main approaches of transforming a BPP into a single-level program (namely the presence of a unique lower level solution, the KKT approach, and the optimal value approach) to derive necessary optimality conditions for BPPs. Furthermore, we comment on the relation between the original BPP and the respective surrogate problem. We apply our findings to formulate necessary optimality conditions for three different classes of BPPs. First, we study a BPP with semidefinite lower level problem possessing a unique solution. Afterwards, we deal with bilevel optimal control problems with dynamical systems of ordinary differential equations at both decision levels. Finally, an optimal control problem of ordinary or partial differential equations with implicitly given pointwise state constraints is investigated.
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Fisch, Florian [Verfasser]. "Development of a Framework for the Solution of High-Fidelity Trajectory Optimization Problems and Bilevel Optimal Control Problems / Florian Fisch." München : Verlag Dr. Hut, 2011. http://d-nb.info/1011441756/34.

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Stibbe, Hilke Isabell [Verfasser], and Ekaterina [Akademischer Betreuer] Kostina. "Special Bilevel Quadratic Problems for Construction of Worst-Case Feedback Control in Linear-Quadratic Optimal Control Problems under Uncertainties / Hilke Isabell Stibbe ; Betreuer: Ekaterina Kostina." Marburg : Philipps-Universität Marburg, 2019. http://d-nb.info/1202110509/34.

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Fisch, Florian [Verfasser], Florian [Akademischer Betreuer] Holzapfel, and Matthias [Akademischer Betreuer] Gerdts. "Development of a Framework for the Solution of High-Fidelity Trajectory Optimization Problems and Bilevel Optimal Control Problems / Florian Fisch. Gutachter: Florian Holzapfel ; Matthias Gerdts. Betreuer: Florian Holzapfel." München : Universitätsbibliothek der TU München, 2011. http://d-nb.info/1013435443/34.

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Palagachev, Konstantin [Verfasser], Matthias [Akademischer Betreuer] Gerdts, Matthias [Gutachter] Gerdts, and Sebastian [Gutachter] Sager. "Mixed-Integer Optimal Control and Bilevel Optimization: Vanishing Constraints and Scheduling Tasks / Konstantin Palagachev ; Gutachter: Matthias Gerdts, Sebastian Sager ; Akademischer Betreuer: Matthias Gerdts ; Universität der Bundeswehr München, Fakultät für Luft- und Raumfahrttechnik." Neubiberg : Universitätsbibliothek der Universität der Bundeswehr München, 2017. http://d-nb.info/1172216533/34.

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Dutto, Rémy. "Méthode à deux niveaux et préconditionnement géométrique en contrôle optimal. Application au problème de répartition de couple des véhicules hybrides électriques." Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSEP088.

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Motivé par le problème industriel de répartition de couple dans les véhicules hybrides électriques, ce travail propose principalement deux nouvelles méthodes de résolution indirectes de problèmes de commande optimale. La première est la méthode Macro-Micro qui est basée sur une décomposition à deux niveaux du problème de commande optimale, faisant intervenir les fonctions valeur de Bellman de manière explicite à des temps préalablement fixés. Ces fonctions sont connues pour être assez difficile à construire. L’idée principale est d’approcher ces fonctions valeur par des réseaux de neurones, ce qui mène à une résolution hiérarchique d’un problème d’optimisation en dimension faible et d’un ensemble de problèmes de commande optimale définis sur des intervalles de temps plus courts. La seconde est une méthode de préconditionnement géométrique qui permet une résolution plus efficace du problème de commande optimale. Cette méthode, basée sur l’interprétation géométrique du co-état et sur la transformée de Mathieu, utilise un changement de variable linéaire à partir de la simple transformation d’une ellipse en cercle. Ces deux méthodes, bien que présentées séparément, peuvent être combinées et mènent à une résolution plus rapide, robuste et légère du problème de répartition de couple, permettant ainsi que de s’approcher des critères d’embarquabilités
Motivated by the torque split and gear shift industrial problem of hybrid electric vehicles, this work mainly proposes two new indirect optimal control problem methods. The first one is the Macro-Micro method, which is based on a bilevel decomposition of the optimal control problem and uses Bellman’s value functions at fixed times. These functions are known to be difficult to create. The main idea of this method is to approximate these functions by neural networks, which leads to a hierarchical resolution of a low dimensional optimization problem and a set of independent optimal control problems defined on smaller time intervals. The second one is a geometric preconditioning method, which allows a more efficient resolution of the optimal control problem. This method is based on a geometrical interpretation of the Pontryagin’s co-state and on the Mathieu transformation, and uses a linear diffeomorphism which transforms an ellipse into a circle. These two methods, presented separately, can be combined and lead together to a fast, robust and light resolution for the torque split and gear shift optimal control problem, closer to the embedded requirements
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Book chapters on the topic "Bilevel optimal control"

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Mehlitz, Patrick, and Gerd Wachsmuth. "Bilevel Optimal Control: Existence Results and Stationarity Conditions." In Bilevel Optimization, 451–84. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52119-6_16.

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Marcotte, Patrice, and Gilles Savard. "A Bilevel Programming Approach to Optimal Price Setting." In Decision & Control in Management Science, 97–117. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3561-1_6.

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Bonnel, Henri, and Jacqueline Morgan. "Optimality Conditions for Semivectorial Bilevel Convex Optimal Control Problems." In Computational and Analytical Mathematics, 45–78. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7621-4_4.

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Dempe, Stephan, Felix Harder, Patrick Mehlitz, and Gerd Wachsmuth. "Analysis and Solution Methods for Bilevel Optimal Control Problems." In International Series of Numerical Mathematics, 77–99. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79393-7_4.

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Palagachev, Konstantin D., and Matthias Gerdts. "Numerical Approaches Towards Bilevel Optimal Control Problems with Scheduling Tasks." In Math for the Digital Factory, 205–28. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63957-4_10.

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Palagachev, Konstantin, and Matthias Gerdts. "Exploitation of the Value Function in a Bilevel Optimal Control Problem." In IFIP Advances in Information and Communication Technology, 410–19. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-55795-3_39.

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Knauer, Matthias, and Christof Büskens. "Hybrid Solution Methods for Bilevel Optimal Control Problems with Time Dependent Coupling." In Recent Advances in Optimization and its Applications in Engineering, 237–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12598-0_20.

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Bock, Hans Georg, Ekaterina Kostina, Marta Sauter, Johannes P. Schlöder, and Matthias Schlöder. "Numerical Methods for Diagnosis and Therapy Design of Cerebral Palsy by Bilevel Optimal Control of Constrained Biomechanical Multi-Body Systems." In International Series of Numerical Mathematics, 21–41. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79393-7_2.

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Conference papers on the topic "Bilevel optimal control"

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Samadi, Sepideh, Daniel Burbano, and Farzad Yousefian. "Achieving Optimal Complexity Guarantees for a Class of Bilevel Convex Optimization Problems." In 2024 American Control Conference (ACC), 2206–11. IEEE, 2024. http://dx.doi.org/10.23919/acc60939.2024.10644364.

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Minciardi, R., and M. Robba. "Bilevel approach for the optimal control of interconnected microgrids." In 2014 IEEE 53rd Annual Conference on Decision and Control (CDC). IEEE, 2014. http://dx.doi.org/10.1109/cdc.2014.7039770.

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Suryan, Varun, Ankur Sinha, Pekka Malo, and Kalyanmoy Deb. "Handling inverse optimal control problems using evolutionary bilevel optimization." In 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2016. http://dx.doi.org/10.1109/cec.2016.7744019.

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Enmin Feng, Zhigang Jiang, Yanjie Li, and Zhilong Xiu. "The Optimal Properties of Nonlinear Bilevel Multi-stage Dynamic System." In 2006 6th World Congress on Intelligent Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/wcica.2006.1712507.

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Tomasi, Matilde, and Alessio Artoni. "Identification of Motor Control Objectives in Human Locomotion via Multi-Objective Inverse Optimal Control." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-89536.

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Abstract Predictive simulations of human motion are a precious resource for a deeper understanding of the motor control policies encoded by the central nervous system. They also have profound implications for the design and control of assistive and rehabilitation devices, for ergonomics, as well as for surgical planning. However, the potential of state-of-the-art predictive approaches is not fully realized yet, making it difficult to draw convincing conclusions about the actual optimality principles underlying human walking. In the present study we propose a novel formulation of a bilevel, inverse optimal control strategy based on a full-body three-dimensional neuromusculoskeletal model. In the lower level, prediction of walking is formulated as a principled multi-objective optimal control problem based on a weighted Chebyshev metric, whereas the contributions of candidate control objectives are systematically and efficiently identified in the upper level. Our framework has proved to be effective in determining the contributions of the selected objectives and in reproducing salient features of human locomotion. Nonetheless, some deviations from the experimental kinematic and kinetic trajectories have emerged, suggesting directions for future research. The proposed framework can serve as an inverse optimal control platform for testing multiple optimality criteria, with the ultimate goal of learning the control objectives that best explain observed human motion.
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Fisch, Florian, Jakob Lenz, Florian Holzapfel, and Gottfried Sachs. "On the Solution of Bilevel Optimal Control Problems to Increase the Fairness in Air Races." In AIAA Atmospheric Flight Mechanics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-7625.

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