Academic literature on the topic 'Single-Leader-Multi-Follower game'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Single-Leader-Multi-Follower game.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Single-Leader-Multi-Follower game":
1
Harks, Tobias, Mona Henle, Max Klimm, Jannik Matuschke, and Anja Schedel. "Multi-Leader Congestion Games with an Adversary." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 5 (June 28, 2022): 5068–75. http://dx.doi.org/10.1609/aaai.v36i5.20439.
Abstract:
We study a multi-leader single-follower congestion game where multiple users (leaders) choose one resource out of a set of resources and, after observing the realized loads, an adversary (single-follower) attacks the resources with maximum loads causing additional costs for the leaders. For the resulting strategic game among the leaders, we show that pure Nash equilibria fail to exist and therefore, we consider approximate equilibria instead. As our first main result, we show that the existence of a K-approximate equilibrium can always be guaranteed, where K (approximately equal to 1.1974) is the unique solution of a cubic polynomial equation. To this end, we give a polynomial time combinatorial algorithm which computes a K-approximate equilibrium. The factor K is tight, meaning that there is an instance that does not admit an A-approximate equilibrium for any A < K. Thus A = K is the smallest possible value of A such that the existence of an A-approximate equilibrium can be guaranteed for any instance of the considered game. Secondly, we focus on approximate equilibria of a given fixed instance. We show how to compute efficiently a best approximate equilibrium, that is, with smallest possible A among all A-approximate equilibria of the given instance.
2
Liu, Lu-Ping, and Wen-Sheng Jia. "An Intelligent Algorithm for Solving the Efficient Nash Equilibrium of a Single-Leader Multi-Follower Game." Mathematics 9, no. 5 (February 24, 2021): 454. http://dx.doi.org/10.3390/math9050454.
Abstract:
This aim of this paper is to provide the immune particle swarm optimization (IPSO) algorithm for solving the single-leader–multi-follower game (SLMFG). Through cooperating with the particle swarm optimization (PSO) algorithm and an immune memory mechanism, the IPSO algorithm is designed. Furthermore, we define the efficient Nash equilibrium from the perspective of mathematical economics, which maximizes social welfare and further refines the number of Nash equilibria. In the end, numerical experiments show that the IPSO algorithm has fast convergence speed and high effectiveness.
3
Kumar, Akhilesh, Anjana Gupta, and Aparna Mehra. "A bilevel game model for ascertaining competitive target prices for a buyer in negotiation with multiple suppliers." RAIRO - Operations Research 56, no. 1 (January 2022): 293–330. http://dx.doi.org/10.1051/ro/2021185.
Abstract:
In this paper, a decision-support is developed for a strategic problem of identifying target prices for the single buyer to negotiate with multiple suppliers to achieve common goal of maintaining sustained business environment. For this purpose, oligopolistic-competitive equilibrium prices of suppliers are suggested to be considered as target prices. The problem of identifying these prices is modeled as a multi-leader-single-follower bilevel programming problem involving linear constraints and bilinear objective functions. Herein, the multiple suppliers are considered leaders competing in a Nash game to maximize individual profits, and the buyer is a follower responding with demand-order allocations to minimize the total procurement-cost. Profit of each supplier is formulated on assessing respective operational cost to fulfill demand-orders by integrating aggregate-production-distribution-planning mechanism into the problem. A genetic-algorithm-based technique is designed in general for solving large-scale instances of the variant of bilevel programming problems with multiple leaders and single follower, and the same is applied to solve the modeled problem. The developed decision support is appropriately demonstrated on the data of a leading FMCG manufacturing firm, which manufactures goods through multiple sourcing.
4
Shi, Chenguang, Wei Qiu, Fei Wang, Sana Salous, and Jianjiang Zhou. "Stackelberg Game-Theoretic Low Probability of Intercept Performance Optimization for Multistatic Radar System." Electronics 8, no. 4 (April 2, 2019): 397. http://dx.doi.org/10.3390/electronics8040397.
Abstract:
In this paper, the problem of Stackelberg game-theoretic low probability of intercept (LPI) performance optimization in multistatic radar system is investigated. The goal of the proposed LPI optimization strategy is to minimize the transmitted power of each radar while satisfying a predetermined signal-to-interference-plus-noise ratio (SINR) requirement for target detection. Firstly, a single-leader multi-follower Stackelberg game is adopted to formulate the LPI optimization problem of multistatic radar system. In the considered game model, the hostile intercept receiver plays a role of leader, who decides the prices of power resource first through the maximization of its own utility function. The multiple radars are followers to compete with each other in a non-cooperative game according to the imposed prices from the intercept receiver subsequently. Then, the Nash equilibrium (NE) for the considered game model is derived, and the existence and uniqueness of the NE are analytically proved. Furthermore, a pricing-based distributed iterative power control algorithm is proposed. Finally, some simulation examples are provided to demonstrate that the proposed scheme has remarkable potential to enhance the LPI performance of the multistatic radar system.
5
Bao, Xiao-Ying, and Lei Zhang. "Green Procurement Relationships Development under Carbon Emissions Regulations: A Bi-Level Programming Approach." International Journal of Environmental Research and Public Health 15, no. 10 (October 6, 2018): 2183. http://dx.doi.org/10.3390/ijerph15102183.
Abstract:
A multi-period Stackelberg game is adopted to study a green procurement relationship between manufacturers and suppliers in a supply chain. The manufacturers are considered as leaders, while the suppliers are modelled as followers in this Stackelberg game. Accordingly, a mixed binary linear bi-level programming model is developed to elaborate the game in consideration of carbon tax scheme. The upper level (the leader) aims at selecting a proper number of suitable suppliers to provide heterogeneous raw materials at the lowest operational cost. The objective of the lower level (the follower) is to find optimal purchasing quantities of raw materials. In addition, two lemmas are introduced to transform the mixed linear bi-level programming model into a single level linear programming model. The numerical example illustrates that: (1) the manufacturer prefers to adopt the multiple sourcing strategy due to the flexibility; (2) keeping stable supplies and large order volumes could effectively reduce carbon emissions for the suppliers and make the supply chain greener.
6
Zuo, Juan, WenBo Wang, and XiangMin Hou. "A two-tier game model based scheduling strategy for Virtual Power Plants." Journal of Physics: Conference Series 2378, no. 1 (December 1, 2022): 012096. http://dx.doi.org/10.1088/1742-6596/2378/1/012096.
Abstract:
Abstract Recently, there has been a lot of attention on how to enhance the management capabilities of distributed electricity production and demand aggregation by Virtual Power Plants (VPPs), which poses the challenge of leveraging their ability to participate in electricity markets to maximize operating profits. This paper analyzes the scheduling problem in fully distributed controlled VPP and proposes a two-level game model. In this model, the Stackelberg game is used to describe the interaction between Distributed Energy Resources (DER) and Energy Management System (EMS). On the other hand, the competition between DERs is formulated by the Cournot game. EMS sets its electric rate as single-leader, and DERs generate the optimal generation capacity accordingly as multi-follower. Then, we analyze and obtain the relationship between the demand and the resource supply to achieve market equilibrium on maximizing the utility of EMS and DERs. Simulation results show the analysis’s correctness and the proposed strategies’ performance improvement.
7
Ganguly, Baishakhi, Biswajit Sarkar, Mitali Sarkar, Sarla Pareek, and Muhammad Omair. "Influence of controllable lead time, premium price, and unequal shipments under environmental effects in a supply chain management." RAIRO - Operations Research 53, no. 4 (September 13, 2019): 1427–51. http://dx.doi.org/10.1051/ro/2018041.
Abstract:
Recently, carbon emission becomes a major issue during transportation of products from one player to another player. Due to the increasing number of single-setup-multi-delivery (SSMD) policies by several industries, fixed and variable transportation cost and carbon emission cost are considered. The aim of the model is to reduce the total cost of supply chain for controlling the lead time and to diminish setup cost by a discrete investment. A premium cost is introduced and Stackelberg game policy is employed to obtain the analytical solution. Some numerical examples are given to validate the model. Sensitivity analysis and managerial insights are given to show the applicability of the model. Finally, the outcomes show that the model minimizes the optimum cost at the optimal values of the decision variables. It is found that the total cost is minimized when the multi-buyer is leader and vendor is follower.
8
Scopelliti, Domenico. "On a Class of Multistage Stochastic Hierarchical Problems." Mathematics 10, no. 21 (October 31, 2022): 4044. http://dx.doi.org/10.3390/math10214044.
Abstract:
In this paper, following the multistage stochastic approach proposed by Rockafellar and Wets, we analyze a class of multistage stochastic hierarchical problems: the Multistage Stochastic Optimization Problem with Quasi-Variational Inequality Constraints. Such a problem is defined in a suitable functional setting relative to a finite set of possible scenarios and certain information fields. The key of this multistage stochastic hierarchical problem turns out to be the nonanticipativity: some constraints have to be included in the formulation to take into account the partial information progressively revealed. In this way, we are able to study real-world problems in which the hierarchical decision processes are characterized by sequential decisions in response to an increasing level of information. As an application of this class of multistage stochastic hierarchical problems, we focus on the study of a suitable Single-Leader-Multi-Follower game.
9
Han, Qi, Guangming Tan, Xiang Fu, Yadong Mei, and Zhenyu Yang. "Water Resource Optimal Allocation Based on Multi-Agent Game Theory of HanJiang River Basin." Water 10, no. 9 (September 4, 2018): 1184. http://dx.doi.org/10.3390/w10091184.
Abstract:
Water scarcity is an important issue in many countries, and it is therefore necessary to improve the efficiency and equality of water resource allocation for decision makers. Based on game theory (GT), a bi-level optimization model is developed from the perspective of a leader-follower relationship among agents (stakeholders) of a river basin in this study, which consists of a single-agent GT-based optimization model of common interest and a multi-agent cooperative GT-based model. The Hanjiang River Basin is chosen as a case study, where there are conflicts among different interest agents in this basin. The results show that the proposed bi-level model could attain the same improvement of common interest by 8%, with the conventional optimal model. However, different from the conventional optimal model, since the individual interests have been considered in the bi-level optimization model, the willingness of cooperation of individuals has risen from 20% to 80%. With a slight decrease by 3% of only one agent, the increases of interest of other agents are 14%, 18%, 7%, and 14%, respectively, when using the bi-level optimization model. The conclusion could be drawn that the proposed model is superior to the conventional optimal model. Moreover, this study provides scientific support for the large spatial scale water resource allocation model.
10
Li, Shiyong, Wenzhe Li, Huan Liu, and Wei Sun. "A Stackelberg Game Approach toward Migration of Enterprise Applications to the Cloud." Mathematics 9, no. 19 (September 22, 2021): 2348. http://dx.doi.org/10.3390/math9192348.
Abstract:
With the development of cloud computing, more and more cloud resources are rented or purchased by users. Using an economics approach to achieve cloud resource management has been thought of as a good choice for an enterprise user to complete an application’s migration and deployment into the public cloud. During an application’s migration process, it is important but very challenging to achieve the satisfaction of both the enterprise user and the public cloud provider at the same time. In this paper, we apply an economics approach to investigate the migration optimization problem during the migration process of applications from the enterprise user’s data center to the remote public cloud. We consider the application migration time of the enterprise user and the energy consumption of physical machines, and establish a single static round optimization problem for both the enterprise user and the cloud provider on the premise of satisfying the quality of experience (QoE) based on the Stackelberg game, where the public cloud provider is leader and the enterprise user is follower. Then we propose a novel algorithm to find the optimal physical machine placement for application migration. After that, we further consider that an enterprise user needs to migrate several applications, and extend the single-round static game to the multi-round dynamic game, where the energy consumption costs of the physical machines are reduced by adjusting the states of the physical machines in each round. We finally illustrate the performance of our scheme through some simulation results.
Dissertations / Theses on the topic "Single-Leader-Multi-Follower game":
1
Lasluisa, Daniel. "Contributions to optimization in energy : from bilevel optimization to optimal design of renewable energy plant." Electronic Thesis or Diss., Perpignan, 2024. http://www.theses.fr/2024PERP0009.
Abstract:
Dans ce travail de thèse, nous développons et appliquons des techniques d'optimisation dans la conception et la gestion de l'énergie. Tout d'abord, nous nous concentrons sur l'optimisation bi-niveaux et développons une nouvelle analyse théorique pour les jeux à un seul meneur et plusieurs suiveurs avec des contraintes de cardinalité. Cette analyse est ensuite appliquée à la localisation optimale des stations de recharge pour véhicules électriques. La deuxième partie est consacrée à l'optimisation économique, à long terme et à court terme, des centrales solaires à concentration. Une approche innovante d'optimisation globale combinant la conception optimale du stockage et l'exploitation optimale dans un contexte de marché est développée. Ensuite, dans un perspective à court terme, le contrôle optimal de la production d'énergie d'une centrale solaire est analyséIn this thesis work, we develop and apply optimization techniques in energy design and management. First we focus on bilevel optimization and developed new theoretical analysis for single-leader-multi-follower games with cardinality constraints. It is then applied to optimal location of charging stations for electric vehicles. The second part is dedicated to economic optimization of solar power plants from a long term as well as from a short term perspective. Innovating global optimization approach mixing optimal design of storage and optimal operation in a market context is developed. Then at a short term scale, the optimal control of energy production of a solar power plant is analysed
En este trabajo de tesis, desarrollamos y aplicamos técnicas de optimización en el dise˜no y gestión de energía. En primer lugar, nos enfocamos en la optimización binivel y desarrollamos nuevo análisis teórico para single-leader-multi-follower games con restricciones de cardinalidad. Luego, se aplica a la localización óptima de estaciones de carga por vehículos eléctricos. La segunda parte está dedicada a la optimización económica de plantas solares desde una perspectiva a largo plazo, así como desde una perspectiva a corto plazo. Se desarrolla un enfoque innovador de optimización global que combina el dise˜no óptimo de almacenamiento y la operación óptima en un contexto de mercado. Luego, a escala a corto plazo, se analiza el control óptimo de la producción de energía de una planta solar
Conference papers on the topic "Single-Leader-Multi-Follower game":
1
Coniglio, Stefano, Nicola Gatti, and Alberto Marchesi. "Pessimistic Leader-Follower Equilibria with Multiple Followers." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/25.
Abstract:
The problem of computing the strategy to commit to has been widely investigated in the scientific literature for the case where a single-follower is present. In the multi-follower setting though, results are only sporadic. In this paper, we address the multi-follower case for normal-form games, assuming that, after observing the leader’s commitment, the followers play pure strategies and reach a Nash equilibrium. We focus on the pessimistic case where, among many equilibria, one minimizing the leader’s utility is chosen (the opposite case is computationally trivial). We show that the problem is NP-hard even with only two followers, and propose an exact exponential-time algorithm which, for any number of followers, either finds an equilibrium when the game admits a finite one or, if not, an α-approximation of the supremum of the leader’ utility, for any α > 0.
2
Panchal, Jitesh H., Marco Gero Ferna´ndez, Janet K. Allen, Christiaan J. J. Paredis, and Farrokh Mistree. "An Interval-Based Focalization Method for Decision-Making in Decentralized, Multi-Functional Design." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85322.
Abstract:
Multi-functional design problems are characterized by strong coupling between design variables that are controlled by stakeholders from different disciplines. This coupling necessitates efficient modeling of interactions between multiple designers who want to achieve conflicting objectives but share control over design variables. Various game-theoretic protocols such as cooperative, non-cooperative, and leader/follower have been used to model interactions between designers. Non-cooperative game theory protocols are of particular interest for modeling cooperation in multi-functional design problems. These are the focus of this paper because they more closely reflect the level of information exchange possible in a distributed environment. Two strategies for solving such non-cooperative game theory problems are: a) passing Rational Reaction Sets (RRS) among designers and combining these to find points of intersection and b) exchanging single points in the design space iteratively until the solution converges to a single point. While the first strategy is computationally expensive because it requires each designer to consider all possible outcomes of decisions made by other designers, the second strategy may result in divergence of the solution. In order to overcome these problems, we present an interval-based focalization method for executing decentralized decision-making problems that are common in multi-functional design scenarios. The method involves propagating ranges of design variables and systematically eliminating infeasible portions of the shared design space. This stands in marked contrast to the successive consideration of single points, as emphasized in current multifunctional design methods. The key advantages of the proposed method are: a) targeted reduction of design freedom and b) non-divergence of solutions. The method is illustrated using two sample scenarios — solution of a decision problem with quadratic objectives and the design of multi-functional Linear Cellular Alloys (LCAs). Implications include use of the method to guide design space partitioning and control assignment.
3
Chen, Yang, Xiao Kou, Mohammed Olama, Helia Zandi, Chenang Liu, Saiid Kassaee, Brennan T. Smith, Ahmad Abu-Heiba, and Ayyoub M. Momen. "Bi-Level Optimization for Electricity Transaction in Smart Community With Modular Pump Hydro Storage." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22368.
Abstract:
Abstract Grid integration of the increasing distributed energy resources could be challenging in terms of new infrastructure investment, power grid stability, etc. To resolve more renewables locally and reduce the need for extensive electricity transmission, a community energy transaction market is assumed with market operator as the leader whose responsibility is to generate local energy prices and clear the energy transaction payment among the prosumers (followers). The leader and multi-followers have competitive objectives of revenue maximization and operational cost minimization. This non-cooperative leader-follower (Stackelberg) game is formulated using a bi-level optimization framework, where a novel modular pump hydro storage technology (GLIDES system) is set as an upper level market operator, and the lower level prosumers are nearby commercial buildings. The best responses of the lower level model could be derived by necessary optimality conditions, and thus the bi-level model could be transformed into single level optimization model via replacing the lower level model by its Karush-Kuhn-Tucker (KKT) necessary conditions. Several experiments have been designed to compare the local energy transaction behavior and profit distribution with the different demand response levels and different local price structures. The experimental results indicate that the lower level prosumers could benefit the most when local buying and selling prices are equal, while maximum revenue potential for the upper level agent could be reached with non-equal trading prices.