基于NSGA-II算法的认知无线电频谱分配

认知无线电中,频谱拍卖是解决动态频谱分配的有效方法,其主要目的是最大化所有主用户的收益。然而,主用户间的收益是存在冲突的,给拍卖算法的优化带来了困难。为此,提出一种新的拍卖方案,来解决获胜者确定问题(Winner Determination Problem, WDP)。在该方案中,动态频谱拍卖问题被建模成多背包问题,并通过非支配排序遗传算法II (NSGA-II)得到最终的解决方案。最后,仿真实验结果表明,就解决WDP问题而言,与贪心算法相比,NSGA-II算法有更好的表现。     

论强制拍卖采矿权中权力的行使

强制拍卖作为法院的一种强制执行措施,应当由法院行使。但是,对于采矿权的强制拍卖,存在诸多争议,其中最重要的一个争议就是强制拍卖的主体是法院还是国土资源主管部门。这一问题的解决涉及对采矿权这一特殊财产权的性质的把握,涉及对法院执行权和强制拍卖的理解,涉及对强制拍卖法律规范与《拍卖法》的关系的认识。本文兼顾学理和法律,认为强制拍卖采矿权适用《民事诉讼法》及相关司法解释,并选择适用《拍卖法》;强制拍卖采矿权的主体是法院,国土资源主管部门负有协助义务。     

Strategy/False-name Proof Protocols for Combinatorial Multi-Attribute Procurement Auction

In this paper, we investigate a model of a combinatorial, procurement multi-attribute auction, in which each sales item is defined by several attributes called quality, the buyer is the auctioneer (e.g., a government), and the sellers are the bidders. Furthermore, there exist multiple items and both buyer and sellers can have arbitrary (e.g., substitutable/complementary) preferences on a bundle of items. Our goal is to develop a protocol that is strategy-proof for sellers. We first present a VickreyClarkeGroves (VCG)-type protocol. As in a standard combinatorial auction, a VCG-type protocol is not false-name-proof, i.e., it is vulnerable against manipulations using multiple identifiers. Next, we show that any strategy-proof protocol in this model can be represented as a framework called Price-Oriented Rationing-Free (PORF) protocol, in which for each bidder, for each bundle of items, and for each quality, the payment for the bidder is determined independently of his own declaration, and the bidder can obtain a bundle that maximizes his utility independently of the allocations of other bidders. We develop a false-name-proof protocol in this model.     

A secure reverse Vickrey auction scheme with bid privacy

In recent years auctions have become more and more important in the field of multi-agent systems as useful mechanisms for resource allocations, task assignments and electronic commerce. In this paper, we concentrate on the use of the reverse Vickrey auction for task assignment scenarios and propose a novel RVP auction protocol as a method to solve problems to bid privacy in reverse Vickrey auctions. A verifiable technique of encryption key chain is used to find the second lowest bid without revealing the losing bid and unnecessary information. Through analysis, it is verified that our new scheme is robust against cheating bidders.     

基于有效性的逆荷兰式拍卖网格资源调度

提出了基于有效的逆荷兰式拍卖算法，用于解决网格计算环境下的网格资源管理和调度，阐述了利用GridSim建立基于有效的逆荷兰式拍卖算法的模拟平台的主要步骤。最后模拟实验表明此算法具有优良的性能。     

MoRVAM: A reverse Vickrey auction system for mobile commerce

Internet auctions bring buyers and sellers together for the purpose of trading goods and services online. In order to get the goods, a buyer must search for items through several auction sites. When the auction starts, the buyer needs to connect to these auction sites frequently so that he/she can monitor the bid states and re-bid. In this paper, we propose an automated negotiation model between two participants, for mobile commerce, using collaborative mobile agents called MoRVAM, which mediates between the buyer and the sellers, and executes bidding asynchronously and autonomously. A new RVT protocol is also implemented to achieve unconditional bid privacy. Advantages of the RVT protocol are addressed as well. All the bidding process can be implemented without revealing losing bid and unnecessary information.     

17世纪荷兰绘画艺术的大众审美特征研究

17世纪荷兰绘画艺术的大众审美特征,在世界艺术发展史上具有里程碑的意义。它不仅预示着现代大众艺术观念的初步确立,而且为现代艺术市场的建立打下了基础。本文从17世纪荷兰绘画艺术大众审美特征产生的原因、在创作中的具体表现和对我国当代艺术发展的启示三方面进行深入剖析,以揭示其中的学术价值和实际借鉴意义。     

基于拍卖机制的改进合同网协商策略

在现有合同网协议的研究基础上，引入经济学中的拍卖理论，提出一种基于拍卖机制的改进合同网协商策略，通过Agent间的自主竞争来实现任务的动态分配，从而降低管理者获取和更新其他Agent知识的难度，间接支持Agent能力动态变化，减少Agent间通讯量和评标时间。     

基于社会清洁福利最大化的电热联合双边竞价市场出清优化策略研究

清洁能源利用和可再生能源消纳是区域电-热综合能源系统研究的重点。基于电-热联合双边竞价市场及其供需侧资源报价策略,提出计及能源碳排放和风机弃风的系统运行环境价值成本概念。同时考虑系统供需侧分布式能源站和多能用户利益,构建以社会清洁福利最大化为目标的市场出清策略模型,确定联合市场交易最优策略。通过算例仿真结果表明,所提市场出清策略模型可以有效促进清洁能源利用和可再生能源消纳,显著降低系统供能过程中造成的环境污染。     

电力市场智能模拟中代理决策模块的实现

在日前交易方式下,发电厂商为了追求长期最大利润,竞价策略显得尤其重要。通常,发电厂商运用的策略过于复杂,难以用传统的博弈论方法来建模。人工智能中强化学习 Q -learning算法是一种自适应的学习方法,使代理能够通过不断与环境进行交互所得到的经验进行学习,适合在电力市场智能模拟中运用。文中在开放源代码的电力市场智能模拟平台AMES上,增加了发电厂商代理基于 Q -learning的竞价决策程序模块,并在5节点测试系统上进行模拟。实验结果表明,运用基于 Q -learning算法竞价决策使代理可以较好地模拟发电厂商的经济特性,且在相同条件下表现出比AMES原有的VRE learning算法更强的探索能力。