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Journal articles on the topic 'BILEVEL PROGRAMMING FRAMEWORK'

Author: Grafiati

Published: 11 September 2023

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1

Ryu, Jun-Hyung, Vivek Dua, and Efstratios N. Pistikopoulos. "A bilevel programming framework for enterprise-wide process networks under uncertainty." Computers & Chemical Engineering 28, no. 6-7 (2004): 1121–29. http://dx.doi.org/10.1016/j.compchemeng.2003.09.021.

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2

Alnowibet, Khalid A., Ahmad M. Alshamrani, and Adel F. Alrasheedi. "A Bilevel Stochastic Optimization Framework for Market-Oriented Transmission Expansion Planning Considering Market Power." Energies 16, no. 7 (2023): 3256. http://dx.doi.org/10.3390/en16073256.

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Market power, defined as the ability to raise prices above competitive levels profitably, continues to be a prime concern in the restructured electricity markets. Market power must be mitigated to improve market performance and avoid inefficient generation investment, price volatility, and overpayment in power systems. For this reason, involving market power in the transmission expansion planning (TEP) problem is essential for ensuring the efficient operation of the electricity markets. In this regard, a methodological bilevel stochastic framework for the TEP problem that explicitly includes t

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3

Park, Minyoung, and Amelia Regan. "Capacity Modeling in Transportation." Transportation Research Record: Journal of the Transportation Research Board 1906, no. 1 (2005): 97–104. http://dx.doi.org/10.1177/0361198105190600112.

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A conceptual framework is presented for modeling the capacity of multimodal freight transportation networks. A review is provided on the evolution of capacity models for use in transportation systems planning and investment, and recent advances toward a system-oriented, multimodal capacity model are discussed in depth. A logical network capacity model based on bilevel programming is proposed.

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Fernandez-Blanco, Ricardo, José M. Arroyo, and Natalia Alguacil. "A Unified Bilevel Programming Framework for Price-Based Market Clearing Under Marginal Pricing." IEEE Transactions on Power Systems 27, no. 1 (2012): 517–25. http://dx.doi.org/10.1109/tpwrs.2011.2161348.

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5

Zang, Guangzhi, Meng Xu, and Ziyou Gao. "High-occupancy Vehicle Lanes and Tradable Credits Scheme for Traffic Congestion Management: A Bilevel Programming Approach." PROMET - Traffic&Transportation 30, no. 1 (2018): 1–10. http://dx.doi.org/10.7307/ptt.v30i1.2300.

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High-occupancy vehicle (HOV) lanes, which are designed so as to encourage more people to use high-capacity travel modes and thus move more people in a single roadway lane, have been implemented as a lane management measure to deal with the growing traffic congestion in practice. However, the implementation has shown that some HOV lanes are not able to achieve the expected effects without proper HOV lane settings. In this study, the tradable credits scheme (TCS) is introduced to improve the HOV lane management and an optimal capacity of HOV lanes in a multilane highway is investigated to match

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6

Chen, Hui-Ju. "A two-level vertex-searching global algorithm framework for bilevel linear fractional programming problems." Systems Science & Control Engineering 8, no. 1 (2020): 488–99. http://dx.doi.org/10.1080/21642583.2020.1805815.

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7

Burgard, Anthony P., Priti Pharkya, and Costas D. Maranas. "Optknock: A bilevel programming framework for identifying gene knockout strategies for microbial strain optimization." Biotechnology and Bioengineering 84, no. 6 (2003): 647–57. http://dx.doi.org/10.1002/bit.10803.

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8

Epshteyn, A., and G. DeJong. "Generative Prior Knowledge for Discriminative Classification." Journal of Artificial Intelligence Research 27 (September 25, 2006): 25–53. http://dx.doi.org/10.1613/jair.1934.

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We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs) to utilize prior knowledge specified in the generative setting. The dual objective of fitting the data and respecting prior knowledge is formulated as a bilevel program, which is solved (approximately) via iterative application of second-order cone programming. To test our approach, we consider the problem of using WordNet (a semantic database of English language) to improve low-sample classification accuracy of new

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9

Yang, Xia, Chenyang Wang, Xiaozheng He, Hedi Zhang, and Guangming Xu. "Location Optimization for Community Smart Parcel Lockers Based on Bilevel Programming." Journal of Advanced Transportation 2023 (June 2, 2023): 1–18. http://dx.doi.org/10.1155/2023/1998188.

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With the rapid development of e-commerce and the dramatic upsurge in direct-to-consumer deliveries, the last-mile problem has become increasingly apparent. With the distinct advantages of bringing economies of scale and providing 24/7 contactless self-service, smart parcel lockers play a critical role in solving the last-mile problem. However, due to a lack of planning, myopia expansion, and an ambiguous profit model, smart parcel locker suppliers in China have been suffering huge economic losses, restricting their further development. In the study, on the basis of an in-depth analysis of the

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10

Kalashnikov, Vyacheslav V., and Roger Z. Ríos-Mercado. "A natural gas cash-out problem: A bilevel programming framework and a penalty function method." Optimization and Engineering 7, no. 4 (2006): 403–20. http://dx.doi.org/10.1007/s11081-006-0347-z.

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11

Baskan, Ozgur. "A Multiobjective Bilevel Programming Model for Environmentally Friendly Traffic Signal Timings." Advances in Civil Engineering 2019 (October 20, 2019): 1–13. http://dx.doi.org/10.1155/2019/1638618.

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Rapid urbanization and mobility needs of road users increase traffic congestion and delay on urban road networks. Thus, local authorities aim to reduce users’ total travel time through providing a balance between traffic volume and capacity. To do this, they optimize traffic signal timings, which is one of the most preferred methods, and thus they can increase the reserve capacity of a road network. However, more travel demand along with more reserve capacity leads to vehicle emissions problem which has become quite dangerous for road users, especially in developing countries. Therefore, this

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12

Haghighi, Yadollah, Bahman Bahmani-Firouzi, and Mehdi Nafar. "A Partnership of Virtual Power Plant in Day-Ahead Energy and Reserve Markets Based on Linearized AC Network-Constrained Unit Commitment Model." International Transactions on Electrical Energy Systems 2022 (September 6, 2022): 1–16. http://dx.doi.org/10.1155/2022/5650527.

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This paper presents coordinated energy management as a virtual power plant (VPP) framework with a wind farm, a storage system, and a demand response program in the transmission network according to the cooperation of VPPs in day-ahead energy and reserve markets. This strategy is based on a bilevel method, where it maximizes the expected VPP revenue in the proposed markets subject to constraints of renewable and flexible sources and the VPP reserve model in the upper-level problem. Also, a market-clearing model based on network-constrained unit commitment (NCUC) is explained in the lower-level

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13

Zhang, Ting, Ting Qu, George Q. Huang, Xin Chen, and Zongzhong Wang. "Sizing, pricing and common replenishment in a headquarter-managed centralized distribution center." Industrial Management & Data Systems 116, no. 6 (2016): 1086–104. http://dx.doi.org/10.1108/imds-08-2015-0343.

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Purpose – Commonly shared logistics services help manufacturing companies to cut down redundant logistics investments while enhance the overall service quality. Such service-sharing mode has been naturally adopted by group companies to form the so-called headquarter-managed centralized distribution center (HQ-CDC). The HQ-CDC manages the common inventories for the group’s subsidiaries and provides shared storage services to the subsidiaries through appropriate sizing, pricing and common replenishment. Apart from seeking a global optimal solution for the whole group, the purpose of this paper i

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14

Yue, Dajun, and Fengqi You. "Stackelberg-game-based modeling and optimization for supply chain design and operations: A mixed integer bilevel programming framework." Computers & Chemical Engineering 102 (July 2017): 81–95. http://dx.doi.org/10.1016/j.compchemeng.2016.07.026.

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15

Zou, Yuan, Dong-ge Li, and Xiao-song Hu. "Optimal Sizing and Control Strategy Design for Heavy Hybrid Electric Truck." Mathematical Problems in Engineering 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/404073.

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Due to the complexity of the hybrid powertrain, the control is highly involved to improve the collaborations of the different components. For the specific powertrain, the components' sizing just gives the possibility to propel the vehicle and the control will realize the function of the propulsion. Definitely the components' sizing also gives the constraints to the control design, which cause a close coupling between the sizing and control strategy design. This paper presents a parametric study focused on sizing of the powertrain components and optimization of the power split between the engin

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16

Tawfik, Christine, and Sabine Limbourg. "Pricing Problems in Intermodal Freight Transport: Research Overview and Prospects." Sustainability 10, no. 9 (2018): 3341. http://dx.doi.org/10.3390/su10093341.

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The aim of this paper is to consider the topic of pricing decisions in the context of intermodal transport as a subject of significant influence on intermodality’s success and the move towards environment friendly modes to bring about a European sustainable transport system. We review the state of research in intermodal pricing from an Operational Research (OR) perspective as a subject with a vital link to energy consumption and sustainability assessment. In particular, we study freight transport within a revenue-maximizing perspective. Driven by the political incentives to enhance its challen

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17

Zhang, Kaike, Xueping Li, and Mingzhou Jin. "Efficient Solution Methods for a General r-Interdiction Median Problem with Fortification." INFORMS Journal on Computing 34, no. 2 (2022): 1272–90. http://dx.doi.org/10.1287/ijoc.2021.1111.

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This study generalizes the r-interdiction median (RIM) problem with fortification to simultaneously consider two types of risks: probabilistic exogenous disruptions and endogenous disruptions caused by intentional attacks. We develop a bilevel programming model that includes a lower-level interdiction problem and a higher-level fortification problem to hedge against such risks. We then prove that the interdiction problem is supermodular and subsequently adopt the cuts associated with supermodularity to develop an efficient cutting-plane algorithm to achieve exact solutions. For the fortificati

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18

Gao, Jiyao, and Fengqi You. "Economic and Environmental Life Cycle Optimization of Noncooperative Supply Chains and Product Systems: Modeling Framework, Mixed-Integer Bilevel Fractional Programming Algorithm, and Shale Gas Application." ACS Sustainable Chemistry & Engineering 5, no. 4 (2017): 3362–81. http://dx.doi.org/10.1021/acssuschemeng.7b00002.

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19

Chen, Lili, Zhen Wang, Fenghua Li, Yunchuan Guo, and Kui Geng. "A Stackelberg Security Game for Adversarial Outbreak Detection in the Internet of Things." Sensors 20, no. 3 (2020): 804. http://dx.doi.org/10.3390/s20030804.

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With limited computing resources and a lack of physical lines of defense, the Internet of Things (IoT) has become a focus of cyberattacks. In recent years, outbreak propagation attacks against the IoT have occurred frequently, and these attacks are often strategical. In order to detect the outbreak propagation as soon as possible, t embedded Intrusion Detection Systems (IDSs) are widely deployed in the IoT. This paper tackles the problem of outbreak detection in adversarial environment in the IoT. A dynamic scheduling strategy based on specific IDSs monitoring of IoT devices is proposed to avo

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20

Alesiani, Francesco. "Implicit Bilevel Optimization: Differentiating through Bilevel Optimization Programming." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 12 (2023): 14683–91. http://dx.doi.org/10.1609/aaai.v37i12.26716.

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Bilevel Optimization Programming is used to model complex and conflicting interactions between agents, for example in Robust AI or Privacy preserving AI. Integrating bilevel mathematical programming within deep learning is thus an essential objective for the Machine Learning community. Previously proposed approaches only consider single-level programming. In this paper, we extend existing single-level optimization programming approaches and thus propose Differentiating through Bilevel Optimization Programming (BiGrad) for end-to-end learning of models that use Bilevel Programming as a layer. B

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21

Borrero, Juan S., Oleg A. Prokopyev, and Denis Sauré. "Learning in Sequential Bilevel Linear Programming." INFORMS Journal on Optimization, January 27, 2022. http://dx.doi.org/10.1287/ijoo.2021.0063.

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We consider a framework for sequential bilevel linear programming in which a leader and a follower interact over multiple time periods. In each period, the follower observes the actions taken by the leader and reacts optimally, according to the follower’s own objective function, which is initially unknown to the leader. By observing various forms of information feedback from the follower’s actions, the leader is able to refine the leader’s knowledge about the follower’s objective function and, hence, adjust the leader’s actions at subsequent time periods, which ought to help in maximizing the

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22

Khorramfar, Rahman, Osman Y. Özaltın, Karl G. Kempf, and Reha Uzsoy. "Managing Product Transitions: A Bilevel Programming Approach." INFORMS Journal on Computing, June 30, 2022. http://dx.doi.org/10.1287/ijoc.2022.1210.

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We model the hierarchical and decentralized nature of product transitions using a mixed-integer bilevel program with two followers, a manufacturing unit and an engineering unit. The leader, corporate management, seeks to maximize revenue over a finite planning horizon. The manufacturing unit uses factory capacity to satisfy the demand for current products. The demand for new products, however, cannot be fulfilled until the engineering unit completes their development, which, in turn, requires factory capacity for prototype fabrication. We model this interdependency between the engineering and

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23

Nisha, Tarannum, Duong Tung Nguyen, and Vijay K. Bhargava. "A Bilevel Programming Framework for Joint Edge Resource Management and Pricing." IEEE Internet of Things Journal, 2022, 1. http://dx.doi.org/10.1109/jiot.2022.3152139.

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24

Kozanidis, George, and Eftychia Kostarelou. "An Exact Solution Algorithm for Integer Bilevel Programming with Application in Energy Market Optimization." Journal of Optimization Theory and Applications, March 20, 2023. http://dx.doi.org/10.1007/s10957-023-02166-8.

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AbstractWe develop an exact cutting plane solution algorithm for a special class of bilevel programming models utilized for optimal price-bidding of energy producers in day-ahead electricity markets. The proposed methodology utilizes a suitable reformulation in which a key prerequisite for global optimality, termed bilevel feasibility, is relaxed. Solving the problem to global optimality involves finding the price-offers of the strategic producer (upper-level decision variables) which maximize his self-profit upon clearing of the market and identification of the optimal energy quantity distrib

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25

Cesarone, Francesco, Lorenzo Lampariello, Davide Merolla, Jacopo Maria Ricci, Simone Sagratella, and Valerio Giuseppe Sasso. "A bilevel approach to ESG multi-portfolio selection." Computational Management Science 20, no. 1 (2023). http://dx.doi.org/10.1007/s10287-023-00458-y.

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AbstractWe rely on bilevel programming to model the problem of financial service providers that, in order to meet stakeholders’ demands and regulatory requirements, aim at incentivizing accounts’ holders to construct ESG-oriented portfolios so that the overall ESG impact of the firm is optimized, while the preferences of accounts’ owners are still satisfied. We analyze this complicated framework from a theoretical point of view and identify sufficient conditions that make it numerically tractable via a novel, specifically tailored algorithm, whose convergence properties are studied. Numerical

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26

Goyal, Akshit, Yiling Zhang, and Chuan He. "Decision Rule Approaches for Pessimistic Bilevel Linear Programs Under Moment Ambiguity with Facility Location Applications." INFORMS Journal on Computing, July 10, 2023. http://dx.doi.org/10.1287/ijoc.2022.0168.

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We study a pessimistic stochastic bilevel program in the context of sequential two-player games, where the leader makes a binary here-and-now decision, and the follower responds with a continuous wait-and-see decision after observing the leader’s action and revelation of uncertainty. We assume that only the information regarding the mean, covariance, and support is known. We formulate the problem as a distributionally robust (DR) two-stage problem. The pessimistic DR bilevel program is shown to be equivalent to a generic two-stage distributionally robust stochastic (nonlinear) program with bot

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27

Biswas, Arpan, Yong Chen, Nathan Gibson, and Christopher Hoyle. "Bilevel Flexible-Robust Optimization for Energy Allocation Problems." ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg 6, no. 3 (2020). http://dx.doi.org/10.1115/1.4046269.

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Abstract A common issue in energy allocation problems is managing the tradeoff between selling surplus energy to maximize short-term revenue, versus holding surplus energy to hedge against future shortfalls. For energy allocation problems, this surplus represents resource flexibility. The decision maker has an option to sell or hold the flexibility for future use. As a decision in the current period can affect future decisions significantly, future risk evaluation of uncertainties is recommended for the current decision in which a traditional robust optimization is not efficient. Therefore, an

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28

Garcia, Daniel J., Mojtaba Mozaffar, Huaqing Ren, et al. "Sustainable Manufacturing With Cyber-Physical Discrete Manufacturing Networks: Overview and Modeling Framework." Journal of Manufacturing Science and Engineering 141, no. 2 (2018). http://dx.doi.org/10.1115/1.4041833.

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Cyber-physical systems (CPS) enable unprecedented communication between product designers and manufacturers. Effective use of these technologies both enables and requires a new paradigm of methods and models to identify the most profitable and environmentally friendly production plans for a manufacturing network. The operating system for cyber-physical manufacturing (OSCM) and the paired network operations administration and monitoring (NOAM) software are introduced. These technologies guide our development of a mixed integer bilevel programming (BP) model that models the hierarchy between des

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29

Tanınmış, Kübra, and Markus Sinnl. "A Branch-and-Cut Algorithm for Submodular Interdiction Games." INFORMS Journal on Computing, May 12, 2022. http://dx.doi.org/10.1287/ijoc.2022.1196.

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Many relevant applications from diverse areas such as marketing, wildlife conservation, and defending critical infrastructure can be modeled as interdiction games. In this work, we introduce interdiction games whose objective is a monotone and submodular set function. Given a ground set of items, the leader interdicts the usage of some of the items of the follower in order to minimize the objective value achievable by the follower, who seeks to maximize a submodular set function over the uninterdicted items subject to knapsack constraints. We propose an exact branch-and-cut algorithm for this

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30

Lin, Shi-Woei, and Januardi Januardi. "Willingness-to-pay experimental model for Stackelberg dual channel pricing decision." International Journal of Retail & Distribution Management, September 27, 2022. http://dx.doi.org/10.1108/ijrdm-10-2021-0495.

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PurposeThis study proposes and demonstrates a novel approach to analyzing customer channel preferences and willingness-to-pay (WTP) in the dual sales channel (DSC) system involving direct online channels and conventional offline retailers, and to how the pricing decisions are made under specific game competition.Design/methodology/approachQuestionnaire survey based on central composite experiment design was utilized to obtain primary data. The model for customer channel preferences and WTP was then built by using multinomial logistic regression. The propensity of a customer to make purchases i

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