Relevant bibliographies by topics / Lagrangian Relaxation (LR)

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Academic literature on the topic 'Lagrangian Relaxation (LR)'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Lagrangian Relaxation (LR)"

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Zeynal, Hossein, Zuhaina Zakaria, and Ahmad Kor. "Improved Lagrangian relaxation generation decision-support in presence of electric vehicles." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (2021): 598–608. https://doi.org/10.11591/ijeecs.v22.i1.pp598-608.

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Decision making strategies for resources available in macro/micro scales have long been a critical argument. Among existing methods to address such a mixed-binary optimization model, Lagrangian relaxation (LR) found universal acceptance by many utilities, offering a fast and accurate answer. This paper aims at retrofitting the solution way of LR algorithm by dint of meta-heuristic cuckoo search algorithm (CSA). When integrating CSA into LR mechanism, a tighter duality gap is catered, representing more accurate feasible solution. The key performance of CSA exhibits a head start over other class
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Zeynal, Hossein, Zuhaina Zakaria, and Ahmad Kor. "Improved Lagrangian relaxation generation decision-support in presence of electric vehicles." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (2021): 598. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp598-608.

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<p><span>Decision making strategies for resources available in macro/micro scales have long been a critical argument. Among existing methods to address such a mixed-binary optimization model, Lagrangian relaxation (LR) found universal acceptance by many utilities, offering a fast and accurate answer. This paper aims at retrofitting the solution way of LR algorithm by dint of meta-heuristic cuckoo search algorithm (CSA). When integrating CSA into LR mechanism, a tighter duality gap is catered, representing more accurate feasible solution. The key performance of CSA exhibits a head s
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Rodrigues, Rafael N., Edson L. da Silva, Erlon C. Finardi, and Fabricio Y. K. Takigawa. "Solving the Short-Term Scheduling Problem of Hydrothermal Systems via Lagrangian Relaxation and Augmented Lagrangian." Mathematical Problems in Engineering 2012 (2012): 1–18. http://dx.doi.org/10.1155/2012/856178.

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This paper addresses the short-term scheduling problem of hydrothermal power systems, which results in a large-scale mixed-integer nonlinear programming problem. The objective consists in minimizing the operation cost over a two-day horizon with a one-hour time resolution. To solve this difficult problem, a Lagrangian Relaxation (LR) based on variable splitting is designed where the resulting dual problem is solved by a Bundle method. Given that the LR usually fails to find a feasible solution, we use an inexact Augmented Lagrangian method to improve the quality of the solution supplied by the
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Hussin, S. M., M. Y. Hassan, L. Wu, M. P. Abdullah, N. Rosmin, and M. A. Ahmad. "Mixed Integer Linear Programming for Maintenance Scheduling in Power System Planning." Indonesian Journal of Electrical Engineering and Computer Science 11, no. 2 (2018): 607. http://dx.doi.org/10.11591/ijeecs.v11.i2.pp607-613.

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This paper discussed the merit of mixed-integer linear programming (MILP)-based approach against Lagrangian relaxation (LR)-based approach in solving generation and transmission maintenance scheduling problem. MILP provides a straightforward solution by formulating coupling constraints equations so that these sub-problems can be solved simultaneously without involving multipliers. In LR-based approach, generation and transmission maintenance scheduling, and security-constrained unit commitment have been solved individually and the integration was realized through a series of multipliers which
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S.M., Hussin, Hassan M.Y., Wu L., Abdullah M.P., Rosmin N., and Ahmad M.A. "Mixed Integer Linear Programming for Maintenance Scheduling in Power System Planning." Indonesian Journal of Electrical Engineering and Computer Science 11, no. 2 (2018): 607–13. https://doi.org/10.11591/ijeecs.v11.i2.pp607-613.

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This paper discussed the merit of mixed-integer linear programming (MILP)- based approach against Lagrangian relaxation (LR)-based approach in solving generation and transmission maintenance scheduling problem. MILP provides a straightforward solution by formulating coupling constraints equations so that these sub-problems can be solved simultaneously without involving multipliers. In LR-based approach, generation and transmission maintenance scheduling, and security-constrained unit commitment have been solved individually and the integration was realized through a series of multipliers which
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Rajamanickam, Subramani, and Vijayalakshmi C. "Design and Analysis of Lagrangian Algorithm for Power Flow System using Renewable Energy Resources." Indonesian Journal of Electrical Engineering and Computer Science 7, no. 2 (2017): 348. http://dx.doi.org/10.11591/ijeecs.v7.i2.pp348-355.

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This paper mainly deals with the implementation of an Lagrangian Relaxation (LR) technique through a Supervisory Control and Data Acquisition (SCADA) system. Maintaining Power Station is not an easy task which to achieve its demand such as regulating inputs monitoring energy losses. In this paper we have introduced novel SCADA based decentralized approach to minimize the loss of the system and optimize the total generation cost. Due to the nonlinearities of Electricity demand and scheduling time, the problem is not solvable with the usual optimization techniques. For getting appropriate soluti
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Filik, Ummuhan Basaran, and Mehmet Kurban. "Feasible Modified Subgradient Method for Solving the Thermal Unit Commitment Problem as a New Approach." Mathematical Problems in Engineering 2010 (2010): 1–11. http://dx.doi.org/10.1155/2010/159429.

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The Lagrangian relaxation- (LR-) based methods are commonly used to solve the thermal unit commitment (UC) problem which is an important subject in power system engineering. The main drawback of this group of methods is the difference between the dual and the primal solutions which gives some significant problems on the quality of the feasible solutions. In this paper, a new approach, feasible modified subgradient (F-MSG) method which does not require finding an unconstrained global minimum of the Lagrangian function and knowing an optimal value of the problem under consideration in order to u
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Wu, Hongyu, Qiaozhu Zhai, Xiaohong Guan, Feng Gao, and Hongxing Ye. "Security-Constrained Unit Commitment Based on a Realizable Energy Delivery Formulation." Mathematical Problems in Engineering 2012 (2012): 1–22. http://dx.doi.org/10.1155/2012/178193.

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Security-constrained unit commitment (SCUC) is an important tool for independent system operators in the day-ahead electric power market. A serious issue arises that the energy realizability of the staircase generation schedules obtained in traditional SCUC cannot be guaranteed. This paper focuses on addressing this issue, and the basic idea is to formulate the power output of thermal units as piecewise-linear function. All individual unit constraints and systemwide constraints are then reformulated. The new SCUC formulation is solved within the Lagrangian relaxation (LR) framework, in which a
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Zhang, Yungui, Huizhao Li, Xue Wang, and Yan Zeng. "A novel approach for solving multi-objective unit commitment based on decompositioncoordination." MATEC Web of Conferences 277 (2019): 03006. http://dx.doi.org/10.1051/matecconf/201927703006.

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Multi-objective unit commitment (MOUC) considers simultaneously both economic and environmental objectives, then finds the best trade off with respect to these objectives. This paper proposes a novel model for MOUC, and a decomposition coordination approach is presented to solve the model. The MOUC model considers environmental objective by introducing a novel penalty term, and it's a quantized term for preference of environmental objective, which could be a basis for carbon tax makers. The model is solved by a decomposition coordination approach, which decomposes the whole system into subsyst
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Hsiao, Chiu-Han, Frank Yeong-Sung Lin, Hao-Jyun Yang, et al. "Optimization-Based Approaches for Minimizing Deployment Costs for Wireless Sensor Networks with Bounded Estimation Errors." Sensors 21, no. 21 (2021): 7121. http://dx.doi.org/10.3390/s21217121.

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As wireless sensor networks have become more prevalent, data from sensors in daily life are constantly being recorded. Due to cost or energy consumption considerations, optimization-based approaches are proposed to reduce deployed sensors and yield results within the error tolerance. The correlation-aware method is also designed in a mathematical model that combines theoretical and practical perspectives. The sensor deployment strategies, including XGBoost, Pearson correlation, and Lagrangian Relaxation (LR), are determined to minimize deployment costs while maintaining estimation errors below
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Book chapters on the topic "Lagrangian Relaxation (LR)"

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Anand, Vishal. "Survivable Mapping of Virtual Networks onto a Shared Substrate Network." In Principles, Methodologies, and Service-Oriented Approaches for Cloud Computing. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2854-0.ch014.

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The virtualization of both servers and substrate networks will enable the future Internet architecture to support a variety of Cloud computing services and architectures, and prevent its ossification. Since multiple virtual networks (VN) or virtual infrastructure (VI) and services now share the resources of the same underlying network in a network virtualization environment, it is important that efficient techniques are developed for the mapping of the VNs onto the substrate network. Furthermore, due to the sharing of resources, the survivable design of VNs is also very important, since now ev
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Conference papers on the topic "Lagrangian Relaxation (LR)"

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Boudreault, Raphaël, and Claude-Guy Quimper. "Improved CP-Based Lagrangian Relaxation Approach with an Application to the TSP." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/190.

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CP-based Lagrangian relaxation (CP-LR) is an efficient optimization technique that combines cost-based filtering with Lagrangian relaxation in a constraint programming context. The state-of-the-art filtering algorithms for the WeightedCircuit constraint that encodes the traveling salesman problem (TSP) are based on this approach. In this paper, we propose an improved CP-LR approach that locally modifies the Lagrangian multipliers in order to increase the number of filtered values. We also introduce two new algorithms based on the latter to filter WeightedCircuit. The experimental results on TS
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