Current Issue : July - September Volume : 2020 Issue Number : 3 Articles : 5 Articles
This paper investigates a Stackelberg differential game between an upstream region and a downstream region for transboundary\npollution control and ecological compensation (EC) in a river basin. Among them, the downstream region as the leader chooses its\nabatement investment level and an ecological compensation rate to encourage upstream investing in water pollution control\nfirstly. After then, the upstream region as the follower determines its abatement investment level to maximize welfare. FFurthermore,\nwe take into consideration the effects of efficiency-improving and cost-reducing learning by doing which are originated\nfrom abatement investment activity of both regions simultaneously. The results show the following. (i) There is an optimal\necological compensation rate and under which a Pareto improvement result can be obtained. (ii) Carrying out EC will shift some\nabatement investment from the downstream region into the upstream region. (iii) The efficiency-improving and cost-reducing\nlearning by doing derived from abatement investment activity of both regions can decrease the optimal ecological compensation\nrate, increase abatement investment,and improve the social welfare....
The Internet gives access to a huge amount of data at the click of a mouse. This is very\nhelpful when consumers are making decisions about which product to buy. However, the final\ndecision to purchase is still generally made by humans who have limited memory and perception.\nThe short list heuristic is often used when there are many offers on the market. Searchers first find\ninformation about offers via the Internet and on this basis choose a relatively small number of\noffers to view in real life. Although such rules are often used in practice, little research has been\ncarried out on determining, for example, what the size of the short list should be depending on the\nparameters of the problem or modelling how the short list heuristic can be implemented when there\nare multiple decision makers. This article presents a game theoretic model of such a search procedure\nwith two players. These two players can be interpreted, for example, as a couple searching for a flat\nor a second-hand car. The model indicates that under such a search procedure the roles of searchers\nshould only be divided when the preferences of the players are coherent or there is a high level of\ngoodwill between them. In other cases, dividing the roles leads to a high level of conflict....
With the growing demand of cloud services, cloud data centers (CDCs) can provide flexible resource provisioning in order to\naccommodate the workload demand. In CDCs, the virtual machine (VM) resource allocation problem is an important and\nchallenging issue to provide efficient infrastructure services. In this paper, we propose a unified resource allocation scheme for\nVMs in the CDC system. To provide a fair-efficient solution, we concentrate on the basic concept of Shapley value and adopt its\nvariations to effectively allocate CDC resources. Based on the characteristics of value solutions, we develop novel CPU, memory,\nstorage, and bandwidth resource allocation algorithms. To practically implement our algorithms, application types are assumed as\ncooperative game players, and different value solutions are applied to optimize the resource utilization. Therefore, our four\nresource allocation algorithms are jointly combined as a novel fourfold game model and take various benefits in a rational way\nthrough the cascade interactions while solving comprehensively some control issues. To ensure the growing demand of cloud\nservices, this feature can leverage the full synergy of different value solutions. To check the effectiveness and superiority of our\nproposed scheme, we conduct extensive simulations. The simulation results show that our algorithms have significant performance\nimprovement compared to the existing state-of-the-art protocols. Finally, we summarize our cooperative game-based\napproach and discuss possible major research issues for the future challenges about the cloud-assisted DC resource\nallocation paradigm....
The diffusion of green agricultural production under intensive management pattern is an interactive process of strategy\ncomparison and learning on complex networks among traditional farmers and new agricultural operation entities. Based on the\ntheory of evolutionary game and complex networks, we construct evolutionary game models on the scale-free networks to\nsimulate the evolution process of green agricultural production under the market mechanism and the government guidance\nmechanism, respectively. The comparison analysis results in different scenarios show that the stable state of the green agricultural\nproduction network is determined by interactions among the subjects. Detailed experimental results indicate that the doublescore\nsystem under government guidance mechanism has a significant effect on the diffusion of the green agricultural production,\nof which the extra reward or penalty obtained from government is crucial. Besides, the diffusion of the green agricultural\nproduction under the market mechanism is mostly affected by the net profit of green agricultural production. These results are of\ngreat significance for increasing efficiency of governmentâ??s incentive and promoting the initiatives of traditional farmers and new\nagricultural operation entities in the green agricultural production....
A method of finding exact solutions of the modified Veselovâ??Novikov (mVN) equation is constructed by Moutard transformations,\nand a geometric interpretation of these transformations is obtained. An exact solution of the mVN equation is found on\nthe example of a higher order Enneper surface, and given transformations are applied in the game theory via Kazakh proverbs in\nterms of trees....
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