公共建筑项目标识布设策略的进化博弈分析

针对公共建筑项目的标识系统布设过程中各利益相关方的博弈行为,建立了管理方和布设方的进化博弈模型及其复制动态方程,讨论并分析了进化稳定策略,探索博弈双方的演化路径和演化规律,依据分析结果提出了一些科学合理地布设标识系统的建议。     

“双碳”目标下政企及第三方检测机构三方演化博弈分析

针对政府低碳规制下,制造商与第三方机构合谋寻租,导致市面上“伪绿色产品”频现等问题,构建由政府监管部门、制造商和第三方检测机构组成的三方参与主体演化博弈模型。在此基础上,探讨各参与主体演化博弈稳定策略组合及实现条件。通过数值仿真分析,阐明制造商寻租及投机成本、生产高绿色和低绿色产品成本差值、第三方检测机构寻租成本及收益、政府监管部门对制造商及第三方机构的奖惩力度等因素对三方参与主体策略选择及系统优化稳定性的影响,以期为“双碳”目标下政府激励与监管政策制定提供参考。     

政府奖惩机制下港口危化品物流监管的三方演化博弈研究

为解决物流监管中企业向第三方专业机构寻租、政府监管缺失等问题,构建港口物流企业、第三方专业机构和港口行政管理部门的三方演化博弈模型,通过求解与数值仿真,揭示物流监管中演化均衡规律。研究表明,港口行政管理部门设定的奖惩机制必须符合对各方的奖励与惩罚之和大于各自投机收益的条件,才能使策略组合(合规运营、拒绝寻租、宽松监管)成为演化稳定策略;增大奖励与惩罚力度均有利于企业合规运营和第三方专业机构拒绝寻租策略的实施,但港政部门的监管意愿随着奖励力度的增大而减小,且随着奖励力度的增大其效果减弱;提升企业的信誉收益,增加寻租成本及政府失职受到的问责也有助于促进企业向合规运营方向的演化。     

基于公众参与的企业排污治理演化博弈分析北大核心CSSCI

企业排污治理是涉及不同主体利益的博弈问题,从公众参与的角度出发,构建以地方政府、排污企业与公众为主体的企业排污治理演化博弈模型,分析影响各博弈主体策略选择与演化的因素,并经求解确立各方行为趋于稳定状态的条件。以江苏常隆农化有限公司等环境污染案为例进行变量关系设定,并就变量对参与主体策略行为的影响做出分析,结果表明:降低地方政府严格监督的成本并加大对地方政府不严格监督的问责、建立公众参与监督的有效途径且做好受损公众的赔偿裁定、降低企业达标排污的成本并加大对排污企业的监督强度和非法排污惩罚力度是推进三方互动,实现企业排污有效治理的关键。     

考虑零售商公平关切的绿色供应链主体行为演化博弈研究

基于演化博弈的相关理论,在绿色供应链运营过程中考虑零售商公平关切行为,构建供应商、零售商与政府的演化博弈模型并进行稳定性分析,结合数值仿真动态研究政府干预成本、补贴与惩罚力度、供应商绿色成本、零售商公平关切系数的变化对供应链成员策略行为演化结果的影响,以期为实现三方利益平衡提供参考。结果表明,供应商绿色成本与零售商公平关切系数对绿色供应链构建的影响呈正相关;政府监管成本对绿色供应链构建的影响呈负相关;政府补贴与惩罚力度对绿色供应链构建的影响具有阶段差异性。     

基于公众参与的企业排污治理演化博弈分析

企业排污治理是涉及不同主体利益的博弈问题,从公众参与的角度出发,构建以地方政府、排污企业与公众为主体的企业排污治理演化博弈模型,分析影响各博弈主体策略选择与演化的因素,并经求解确立各方行为趋于稳定状态的条件。以江苏常隆农化有限公司等环境污染案为例进行变量关系设定,并就变量对参与主体策略行为的影响做出分析,结果表明:降低地方政府严格监督的成本并加大对地方政府不严格监督的问责、建立公众参与监督的有效途径且做好受损公众的赔偿裁定、降低企业达标排污的成本并加大对排污企业的监督强度和非法排污惩罚力度是推进三方互动,实现企业排污有效治理的关键。     

重大工程组织学习机制的演化博弈分析——基于全过程咨询介入机制的业主与咨询方合作视角

"绩效悖论"是重大工程建设管理的重要难题,如何提升业主方的管理能力成为应对这一难题的重要研究方向。通过跨组织学习理论分析业主与咨询方合作,用演化博弈研究方法建立了业主与咨询方合作过程中双方合作学习的支付矩阵,揭示了双方的行为策略对双方合作学习的影响。借助MATLAB仿真工具揭示混合策略下不同参数变化对其演化结果的影响。最后,研究针对当前国家全过程咨询推广政策的实施提出了积极的建议。     

基于互联网环境的生鲜农产品质量安全控制研究

针对生鲜农产品质量安全问题,构建了基于互联网环境下农户、龙头企业、消费者的三方演化博弈模型,探讨三方主体行为策略的演化过程以及策略选择的相互影响。通过求解稳定均衡点,分析了不同情形下生鲜农产品质量安全三方主体的演化路径,并使用Matlab进行算例分析。研究发现,生鲜农产品质量安全三方演化博弈模型存在多重演化稳定策略,且存在相应的演化稳定条件。据此提出了促使农户和龙头企业提供优质安全生鲜农产品的相关建议,为提高生鲜农产品质量安全水平提供了一个方向。     

供应链节点企业间信任行为的进化博弈

从博弈参与者的有限理性出发,运用"复制动态"机制分析供应链节点企业的学习与调整过程,绘制了供应链节点企业信任行为进化博弈复制动态相图.基于此相图对供应链节点企业选择信任与否的影响因素进行了简要分析.     

政府奖惩激励下快递包装回收行为演化博弈与仿真分析

目的 厘清快递包装废弃物回收利益主体间的博弈关系与演化路径,解决快递包装回收率普遍较低的问题。方法 在信息不对称和有限理性的条件下,构建政府、回收商和消费者三群体间快递包装回收行为演化博弈模型。分析群体间稳定策略组合的实现条件,运用Matlab软件进行数值仿真,探究不同参数变化对三方演化路径的影响。结果 政府的奖惩力度、激励成本、收益大小是影响博弈三主体策略选择和演化稳定路径走向的关键因素。同时回收商和消费者的参与比例对政府行为选择有显著作用。结论 参与主体得益是影响其行为的关键,政府通过积极鼓励、支持和宣传,同时设立科学合理的奖惩激励政策能够明显提高快递包装回收率。     

Handling constraints using multiobjective optimization concepts

In this paper, we propose a new constraint‐handling technique for evolutionary algorithms which we call inverted‐shrinkable PAES (IS‐PAES). This approach combines the use of multiobjective optimization concepts with a mechanism that focuses the search effort onto specific areas of the feasible region by shrinking the constrained search space. IS‐PAES also uses an adaptive grid to store the solutions found, but has a more efficient memory‐management scheme than its ancestor (the Pareto archived evolution strategy for multiobjective optimization). The proposed approach is validated using several examples taken from the standard evolutionary and engineering optimization literature. Comparisons are provided with respect to the stochastic ranking method (one of the most competitive constraint‐handling approaches used with evolutionary algorithms currently available) and with respect to other four multiobjective‐based constraint‐handling techniques. Copyright© 2004 John Wiley & Sons, Ltd.     

基于演化博弈论的可变导向车道设置策略研究

可变导向车道的设置，在提高道路通行效率的同时会造成驾驶人情绪紧张或者因不了解路况导致违规甚至发生事故，对交通系统的安全和稳定运行产生负面影响。以交管部门设置可变导向车道的策略选择为研究目标，结合驾驶人走可变导向车道时产生的紧张情绪损失等因素，构建交管部门−驾驶人群体两方博弈模型。采用演化博弈论的方法分析博弈双方选择行为演化和稳定策略，对系统中存在的5个演化均衡点进行分析，得到系统的3种理想稳定状态和相对应的参数条件，为交管部门设置可变导向车道进行策略选择提供理论支撑。     

Optimization of Reliability–Redundancy Allocation Problems: A Review of the Evolutionary Algorithms

The study of optimization methods for reliability–redundancy allocation problems is a constantly changing field. New algorithms are continually being designed on the basis of observations of nature, wildlife, and humanity. In this paper, we review eight major evolutionary algorithms that emulate the behavior of civilization, ants, bees, fishes, and birds (i.e., genetic algorithms, bee colony optimization, simulated annealing, particle swarm optimization, biogeography-based optimization, artificial immune system optimization, cuckoo algorithm and imperialist competitive algorithm). We evaluate the mathematical formulations and pseudo-codes of each algorithm and discuss how these apply to reliability–redundancy allocation problems. Results from a literature survey show the best results found for series, series–parallel, bridge, and applied case problems (e.g., overspeeding gas turbine benchmark). Review of literature from recent years indicates an extensive improvement in the algorithm reliability performance. However, this improvement has been difficult to achieve for high-reliability applications. Insights and future challenges in reliability–redundancy allocation problems optimization are also discussed in this paper.     

Corruption drives the emergence of civil society

Centralized sanctioning institutions have been shown to emerge naturally through social learning, displace all other forms of punishment and lead to stable cooperation. However, this result provokes a number of questions. If centralized sanctioning is so successful, then why do many highly authoritarian states suffer from low levels of cooperation? Why do states with high levels of public good provision tend to rely more on citizen-driven peer punishment? Here, we consider how corruption influences the evolution of cooperation and punishment. Our model shows that the effectiveness of centralized punishment in promoting cooperation breaks down when some actors in the model are allowed to bribe centralized authorities. Counterintuitively, a weaker centralized authority is actually more effective because it allows peer punishment to restore cooperation in the presence of corruption. Our results provide an evolutionary rationale for why public goods provision rarely flourishes in polities that rely only on strong centralized institutions. Instead, cooperation requires both decentralized and centralized enforcement. These results help to explain why citizen participation is a fundamental necessity for policing the commons.     

Computability,G?del's incompleteness theorem,and an inherent limit on the predictability of evolution

The process of evolutionary diversification unfolds in a vast genotypic space of potential outcomes. During the past century, there have been remarkable advances in the development of theory for this diversification, and the theory''s success rests, in part, on the scope of its applicability. A great deal of this theory focuses on a relatively small subset of the space of potential genotypes, chosen largely based on historical or contemporary patterns, and then predicts the evolutionary dynamics within this pre-defined set. To what extent can such an approach be pushed to a broader perspective that accounts for the potential open-endedness of evolutionary diversification? There have been a number of significant theoretical developments along these lines but the question of how far such theory can be pushed has not been addressed. Here a theorem is proven demonstrating that, because of the digital nature of inheritance, there are inherent limits on the kinds of questions that can be answered using such an approach. In particular, even in extremely simple evolutionary systems, a complete theory accounting for the potential open-endedness of evolution is unattainable unless evolution is progressive. The theorem is closely related to Gödel''s incompleteness theorem, and to the halting problem from computability theory.     

Multi-objective analysis of a component-based representation within an interactive evolutionary design system

This article describes research relating to a user-centered evolutionary design system that evaluates both engineering and aesthetic aspects of design solutions during early-stage conceptual design. The experimental system comprises several components relating to user interaction, problem representation, evolutionary search and exploration and online learning. The main focus of the article is the evolutionary aspect of the system when using a single quantitative objective function plus subjective judgment of the user. Additionally, the manner in which the user-interaction aspect affects system output is assessed by comparing Pareto frontiers generated with and without user interaction via a multi-objective evolutionary algorithm (MOEA). A solution clustering component is also introduced and it is shown how this can improve the level of support to the designer when dealing with a complex design problem involving multiple objectives. Supporting results are from the application of the system to the design of urban furniture which, in this case, largely relates to seating design.     

基于博弈理论的供应链信任稳定演化策略

考虑供应链信任演化3个不同阶段,研究供应链信任稳定演化策略。针对传统博弈的局限性,从约束机制不健全和约束机制健全两个层面进行分析,将企业选择信任的额外收益、单方面信任成本、单方面不信任额外收益、单方面不信任代价和单方面信任额外补偿引入到演化博弈矩阵中,利用演化博弈理论分析各阶段的稳定状态。为验证模型的有效性和可行性,通过数值分析,研究模型的演化动力变化,得出相应的系统相图。研究结果表明,供应链信任策略值的概率大于0.75时,合作达到稳态,供应链整体收益最大;约束机制不健全下的稳定演化策略明显优于传统博弈下的稳定演化策略,但是约束机制不健全,企业的稳定演化策略未必都是信任;供应链企业间需要健全约束机制,当约束机制健全时,信任是企业最终策略选择。     

模糊数学方法在机械设计中的应用

本文应用模糊数学理论,针对模糊设计计算问题,提出了基于模糊数的设计计算方法,并给出了具体的设计计算实例。     

Evolutionary algorithms for solving the automatic cell planning problem: a survey

Automatic cell planning (ACP) is an optimization problem from the mobile telecommunications domain that addresses finding the location of the network antennae as well as their parameter settings in order to satisfy several cellular operator requirements. Due to its NP-hard complexity, evolutionary techniques have become popular for solving ACP instances. This article presents a survey of evolutionary algorithms (EAs) engineered for addressing ACP problems, analysing both the features of the considered ACP problem and the main aspects of the EAs used to solve them. The survey provides an up-to-date overview that is not limited to any particular kind of evolutionary approach, and comprises advanced algorithmic enhancements like hybridization and parallelization. The article ends by addressing some important issues and open questions that can be the subject of future research.