Cloud Provider's Response to Multiple Models of Attack Behaviors

2019 ◽  
Vol 13 (4) ◽  
pp. 325-333
Author(s):  
Xu Liu ◽  
Xiaoqiang Di ◽  
Jinqing Li ◽  
Huamin Yang ◽  
Ligang Cong ◽  
...  
Keyword(s):  
Stackelberg Game ◽  
Multiple Models ◽  
Theoretic Model ◽  
Cloud Provider ◽  
Game Model ◽  
Attack Behavior ◽  
Behavior Model ◽  
Protection Strategy ◽  
Behavior Models ◽  
Optimal Protection

Background: User behavior models have been widely used to simulate attack behaviors in the security domain. We revised all patents related to response to attack behavior models. How to decide the protected target against multiple models of attack behaviors is studied. Methods: We utilize one perfect rational and three bounded rational behavior models to simulate attack behaviors in cloud computing, and then investigate cloud provider’s response based on Stackelberg game. The cloud provider plays the role of defender and it is assumed to be intelligent enough to predict the attack behavior model. Based on the prediction accuracy, two schemes are built in two situations. Results: If the defender can predict the attack behavior model accurately, a single-objective game model is built to find the optimal protection strategy; otherwise, a multi-objective game model is built to find the optimal protection strategy. Conclusion: The numerical results prove that the game theoretic model performs better in the corresponding situation.

scholarly journals Single-Manufacturer Multi-Retailer Supply Chain Models with Discrete Stochastic Demand

2021 ◽  
Vol 13 (15) ◽  
pp. 8271
Author(s):  
Yaqing Xu ◽  
Jiang Zhang ◽  
Zihao Chen ◽  
Yihua Wei
Keyword(s):  
Dynamic Programming ◽  
Supply Chain ◽  
Computational Complexity ◽  
Stackelberg Game ◽  
Programming Model ◽  
Dynamic Programming Method ◽  
Game Model ◽  
Chain Model ◽  
Stochastic Demands ◽  
Demand Models

Although there are highly discrete stochastic demands in practical supply chain problems, they are seldom considered in the research on supply chain systems, especially the single-manufacturer multi-retailer supply chain systems. There are no significant differences between continuous and discrete demand supply chain models, but the solutions for discrete random demand models are more challenging and difficult. This paper studies a supply chain system of a single manufacturer and multiple retailers with discrete stochastic demands. Each retailer faces a random discrete demand, and the manufacturer utilizes different wholesale prices to influence each retailer’s ordering decision. Both Make-To-Order and Make-To-Stock scenarios are considered. For each scenario, the corresponding Stackelberg game model is constructed respectively. By proving a series of theorems, we transfer the solution of the game model into non-linear integer programming model, which can be easily solved by a dynamic programming method. However, with the increase in the number of retailers and the production capacity of manufacturers, the computational complexity of dynamic programming drastically increases due to the Dimension Barrier. Therefore, the Fast Fourier Transform (FFT) approach is introduced, which significantly reduces the computational complexity of solving the supply chain model.

scholarly journals Pricing Policies in a Retailer Stackelberg O2O Green Supply Chain

2020 ◽  
Vol 12 (8) ◽  
pp. 3236
Author(s):  
Gan Wan ◽  
Gang Kou ◽  
Tie Li ◽  
Feng Xiao ◽  
Yang Chen
Keyword(s):  
Supply Chain ◽  
Stackelberg Game ◽  
Good Combination ◽  
Green Supply Chain ◽  
Game Model ◽  
Mathematical Function ◽  
Pricing Strategies ◽  
Direct Channel ◽  
Retail Channel ◽  
Offline Channels

Due to the popularization of the concept of “new retailing”, we study a new commercial model named O2O (online-to-offline), which is a good combination model of a direct channel and a traditional retail channel. We analyze an O2O supply chain in which manufacturers are responsible for making green products and selling them through both online and offline channels. The retailer is responsible for all online and offline channels’ orders, and the manufacturer gives the retailer a fixed fee. We construct a mathematical function model and analyze the greenness and pricing strategies of centralized and decentralized settings through the retailer Stackelberg game model. Due to the effects of the double marginalization of supply chain members, we adopt a simple contract to coordinate the green supply chain. The paper’s contributions are that we obtain pricing and greening strategies by taking the cooperation of offline channels and online channels into consideration under the O2O green supply chain environment.

Revenue Sharing Contract of Green Supply Chain under Manufacturer Risk-Aversion

2014 ◽  
Vol 697 ◽  
pp. 482-487
Author(s):  
Shi Ying Jiang ◽  
Chun Yan Ma
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Risk Aversion ◽  
Stackelberg Game ◽  
Wholesale Price ◽  
Revenue Sharing ◽  
Green Supply Chain ◽  
Game Model ◽  
Product Price ◽  
Revenue Sharing Contract

Background on two stages green supply chain consisting of a manufacturer and a retailer, considering the degree of risk aversion and product greenness, consumer preferences and other factors, the centralized decision-making game model and manufacturer-leading Stackelberg game model are established.Then two game models are compared. The interaction of product greenness, wholesale price, product price,and risk aversion utility for manufacturers and retailers are also disscussed. Finally, the revenue sharing contract is applied to coordinate the green supply chain . The results show that:(1) In the centralized decision-making model, there is a critical value of the product green degree; (2)In manufacturer-leading Stackelberg game model, the higher the green degree of the product, the higher the manufacturer's wholesale price,and the wholesale price increases as risk aversion degree of manufacturers improves;(3)The revenue sharing contract can coordinate this type of green supply chain under manufacturers risk-averse.

Manufacturing service order allocation in the context of social manufacturing based on Stackelberg game

2018 ◽  
Vol 233 (8) ◽  
pp. 1890-1901
Author(s):  
Wei Guo ◽  
Pingyu Jiang
Keyword(s):  
Quality Of Service ◽  
Nash Equilibrium ◽  
Manufacturing Industry ◽  
Stackelberg Game ◽  
Game Model ◽  
Service Cost ◽  
Order Allocation ◽  
Multi Objective ◽  
Bird Swarm Algorithm

For adapting the socialization, individuation and servitization in manufacturing industry, a new manufacturing paradigm called social manufacturing has received a lot of attention. Social manufacturing can be seen as a network that enterprises with socialized resources self-organized into communities that provide personalized machining and service capabilities to customers. Since a community of social manufacturing has multiple enterprises and emphasizes on the importance of service, manufacturing service order allocation must be studied from the new perspective considering objectives on service cost and quality of service. The manufacturing service order allocation can be seen as a one-to-many game model with multi-objective. In this article, a Stackelberg game model is proposed to tackle the manufacturing service order allocation problem with considering the payoffs on cost and quality of service. Since this Stackelberg game can be mapped to a multi-objective bi-level programming, a modified multi-objective hierarchical Bird Swarm Algorithm is used to find the Nash equilibrium of the game. Finally, a case from a professional printing firm is analyzed to validate the proposed methodology and model. The objective of this research is to find the Nash equilibrium on the manufacturing service order allocation and provide strategies guidance for customer and small- and medium-sized enterprises with optimal service cost and lead time. According to the game process and Nash equilibrium, some rules are revealed, and they are useful for guiding practical production.

scholarly journals Research on Pricing Decision of Direct Sales Green Supply Chain Based on Consumers’ Valuation

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yong-Gang Ye ◽  
Xiao-Feng Liu
Keyword(s):  
Supply Chain ◽  
Simulation Analysis ◽  
Stackelberg Game ◽  
Game Model ◽  
Direct Sales ◽  
Equilibrium Prices ◽  
Theoretical Support ◽  
Pricing Decision ◽  
Negative Effect ◽  
Product Valuation

Consumer’s valuation of merchandise is an important factor affecting consumer buying behavior. When the consumer’s valuation exceeds the price of product, the consumer generally makes a decision to purchase the product; conversely, when the consumer’s estimate is lower than the price of product, the consumer will usually refuse to buy the product. From the perspective of consumer product valuation, this study assumed that the consumer’s product valuation obeys a uniform distribution, and a novel consumer demand function was proposed. On this basis, we studied enterprises’ pricing decisions in the supply chain of green agricultural products and obtained the equilibrium prices and optimal profits of the enterprises in several different scenarios, including Vertical Nash game model (VNM), firm A Stackelberg game model (FASM), firm B Stackelberg game model (FBSM), and cooperative game model (CM). In addition, the influence of parameters, such as green level, green preference payment coefficient, and green cost on the optimal profit, was discussed based on game theory and numerical simulation analysis. It was found that equilibrium prices always existed in several different scenarios, and when consumer’s green preference payment coefficient was large enough, the optimal profit of firm B was greater than the optimal profit of firm A. Furthermore, in CM, the sum of optimal profit of firm A and optimal profit of firm B is maximum for four scenarios. Finally, in the three competitive scenarios, green level, green preference payment coefficient, and green cost, have a positive or negative effect on the optimal profits of firm A or firm B. The research conclusions of this study provided theoretical support for the decision-making of enterprises and related management departments.

scholarly journals Dynamic SPICE-model of resource allocation in marketing networks

2020 ◽  
Vol 13 ◽  
pp. 8-23
Author(s):  
Movlatkhan T. Agieva ◽  
◽  
Olga I. Gorbaneva ◽  
Keyword(s):  
Resource Allocation ◽  
Stackelberg Game ◽  
Target Audience ◽  
Opinion Leaders ◽  
Stackelberg Equilibrium ◽  
Common Interest ◽  
Theoretic Model ◽  
Goods And Services ◽  
Spice Model ◽  
Private Interests

We consider a dynamic Stackelberg game theoretic model of the coordination of social and private interests (SPICE-model) of resource allocation in marketing networks. The dynamics of controlled system describes an interaction of the members of a target audience (basic agents) that leads to a change of their opinions (cost of buying the goods and services of firms competing on a market). An interaction of the firms (influence agents) is formalized as their differential game in strategic form. The payoff functional of each firm includes two terms: the summary opinion of the basic agents with consideration of their marketing costs (a common interest of all firms), and the income from investments in a private activity. The latter income is described by a linear function. The firms exert their influence not to all basic agents but only to the members of strong subgroups of the influence digraph (opinion leaders). The opinion leaders determine the stable final opinions of all members of the target audience. A coordinating principal determines the firms' marketing budgets and maximizes the summary opinion of the basic agents with consideration of the allocated resources. The Nash equilibrium in the game of influence agents and the Stackelberg equilibrium in a general hierarchical game of the principal with them are found. It is proved that the value of opinion of a basic agent is the same for all influence agents and the principal. It is also proved that the influence agents assign less resources for the marketing efforts than the principal would like.

Stackcelberg Game Inventory Model With Progressive Permissible Delay of Payment Scheme

2018 ◽  
pp. 194-214
Author(s):  
Gede Agus Widyadana ◽  
Nita H. Shah ◽  
Daniel Suriawidjaja Siek
Keyword(s):  
Genetic Algorithm ◽  
Interest Rate ◽  
Stackelberg Game ◽  
Hybrid Genetic Algorithm ◽  
Inventory Model ◽  
Delay Period ◽  
Game Model ◽  
Inventory Cost ◽  
Swarm Optimization ◽  
High Interest Rate

Supplier has many schemes to motivate retailer to buy more and of them one is a progressive permissible delay of payment. Instead of analyst from the retailer side alone, in this chapter, we develop the inventory model of supplier and retailer. In reality, some suppliers and retailers cannot have collaboration and they try to optimize their own decision so we develop a Stackelberg Game model. Two models are developed wherein the first model supplier acts as the leader and in the second model, the retailer acts a leader. Since the models are complex, a hybrid Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) is developed to solve the model. A numerical analysis and sensitivity analysis are conducted to get management insights of the model. The results show that a Stackelberg Game model for progressive permissible delay of payment is sensitive in varies values of the first and second delay interest rate if supplier acts as a leader. The retailer gets less inventory cost when he acts as a leader compared to when vendor acts a leader at high interest rate of the first and second delay period.

Sign in / Sign up

Export Citation Format

Share Document