一种新的曲线光顺优化模型

对曲线光顺的优化模型进行了讨论，并对直接根据型值点列进行曲线光顺处理的方法进行了研究，提出一种新的优化模型，利用进化规划对曲线光顺问题进行了求解，取得了良好的效果，理论分析和计算实例表明，进化规划算法和文中提出的优化模型是对曲线进行光顺的有效方法。     

基于列车用户优先级的频谱共享博弈算法

不同业务优先级高速铁路用户的爆炸式业务需求与稀缺频谱资源的矛盾日益突出。针对运行于不同地形环境、在相同eNB覆盖范围内的高速铁路次用户的频谱共享博弈问题进行研究。基于次用户承载业务的不同优先级,提出模糊综合评判-优先级调度算法,将次用户间的频谱竞争建模为非合作博弈,通过次服务的频谱效用函数、主系统的频谱交易价格函数实现次用户间的差异化动态频谱共享。仿真结果表明,算法较好地反映了真实的频谱共享情形,可以更加准确地对次用户频谱需求进行业务优先级划分,提高频谱利用率的同时保证了其最大效用。     

信号博弈下的交叉口TSCA间的协调学习模型的构建

针对路网中交叉口之间交通流的关联性、动态性及不确定性，应用了信号博弈作为交叉口交通信号控制agent（TSCA）间协调的模型，以分布式Q强化学习中Q值更新来进行其效用函数的学习，通过引入记忆因子对奖惩函数进行设计，及相邻交叉口之间的影响建立权值函数，构建了协调学习的仿真实现流程，并通过实验仿真验证此模型的有效性。     

Game-theoretical models for competition analysis in a new emerging liner container shipping market

This paper develops three game-theoretical models to analyze shipping competition between two carriers in a new emerging liner container shipping market. The behavior of each carrier is characterized by an optimization model with the objective to maximize his payoff by setting optimal freight rate and shipping deployment (a combination of service frequency and ship capacity setting). The market share for each carrier is determined by the Logit-based discrete choice model. Three competitive game strategic interactions are further investigated, namely, Nash game, Stackelberg game and deterrence by taking account of the economies of scale of the ship capacity settings. Three corresponding competition models with discrete pure strategy are formulated as the variables in shipment deployment are indivisible and the pricing adjustment is step-wise in practice. A ɛ -approximate equilibrium and related numerical solution algorithm are proposed to analyze the effect of Nash equilibrium. Finally, the developed models are numerically evaluated by a case study. The case study shows that, with increasing container demand in the market, expanding ship capacity setting is preferable due to its low marginal cost. Furthermore, Stackelberg equilibrium is a prevailing strategy in most market situations since it makes players attain more benefits from the accommodating market. Moreover, the deterrence effects largely depend on the deterrence objective. An aggressive deterrence strategy may make potential monopolist suffer large benefit loss and an easing strategy has little deterrence effect.     

Myopic loss aversion in the response of electric vehicle owners to the scheduling and pricing of vehicle charging

Upward expectations of future electric vehicle (EV) growth pose the question about the future load on the electricity grid. While existing literature on EV charging demand management has focused on technical aspects and considered EV-owners as utility maximizers, this study proposes a behavioural model incorporating psychological aspects relevant to EV-owners facing charging decisions and interacting with the supplier. The behavioural model represents utility maximization under myopic loss aversion (MLA) within an ultimatum game (UG) framework where the two players are the EV-owner and the electricity supplier. Experimental economics allowed testing the validity of the behavioural model by designing three experiments where a potential EV-owner faces three decisions (i.e., to postpone EV charging to off-peak periods for a discount proposed by the supplier, the amount of discount to request for off-peak charging at times decided by the supplier, and the amount of discount to accept for supplier-controlled charging) under two contract durations (i.e., short-term, long-term). Findings from the experiments show that indeed potential EV-owners perform charging decisions while being affected by MLA resulting from monetary considerations and the UG participation, and that presenting long-term contracts help potential EV-owners to curtail MLA behaviour and minimise cost even though the assumption of utility maximization is violated.     

基于人工智能的兵棋推演作战分析研究与设计

20世纪,随着计算机的出现,使得繁琐、严格的兵棋规则可以在计算机中处理,冯·莱斯威茨父子发明的兵棋迎来了新的春天。论文首先从战斗力度量、战斗结果裁判两方面详细分析了兵棋推演与其它战争分析方法的联系,并总结了兵棋推演应用于战争分析的实践意义。接着以兵棋推演为基础,介绍了相关的对策论、有信息的对抗搜索和局部优化搜索等人工智能技术。最后以一个战术想定为背景,详细阐述了设计兵棋系统时应用人工智能需要解决的数字化、博弈树生成和局面评估等问题。     

基于企业社会责任的航空服务商选择博弈模型

提出了企业社会责任的概念,界定了航空服务商社会责任履行水平与履行力度。将供应链核心企业与航空服务商的博弈情形分为4种,构建了基于企业社会责任的航空服务商选择博弈模型,计算了供应链核心企业的长、短期合作的临界合作意愿与航空服务商的长、短期合作的临界履行概率,分析了企业社会责任履行水平与航空服务商选择之间的关系。分析结果表明:当航空服务商社会责任履行水平为0.5时,供应链核心企业要求普通航空服务商社会责任的履行概率大于40%,要求战略航空服务商社会责任的履行概率大于80%;当供应链核心企业的合作意愿大于41.67%时,普通航空服务商就会积极履行企业社会责任,当供应链核心企业的合作意愿大于83.33%时,战略航空服务商才会积极履行企业社会责任;当航空服务商的社会责任履行水平分别为0.1、0.2、0.3、0.4、0.5、0.6、0.7、0.8、0.9时,供应链核心企业要求战略航空服务商的社会责任履行概率依次大于94.6%、90.0%、86.2%、82.6%、80.0%、77.5%、75.3%、73.3%、71.6%。与传统的方法相比,提出的模型不仅能够明确普通航空服务商与战略航空服务商的不同具体要求,而且揭示了企业社会责任履行水平与战略航空服务商选择之间的实质关系。     

基于博弈论的高速公路网络关键路段识别方法

高速公路网络的关键路段识别对于网络的正常运营及潜在危险的评估具有重要意义。作为交通管理者,需要帮助出行者进行路径的选择策略以尽可能的规避风险并实现出行;而各种潜在威胁,以基于路段失效的策略尽可能地使网络服务能力降低,达到攻击网络的目的。将影响高速公路网络性能的潜在威胁看作网络的攻击者,与交通管理者构成攻防博弈的关系,构建了高速公路网络关键路段识别的攻防博弈模型,实现网络关键路段识别与交通流量分配的同步改善。引入加权熵函数,以表征网络攻击者发出攻击网络的信息的不确定性,结合用户均衡分配方法,提出了该博弈模型的求解算法。黑龙江省高速公路网络的算例结果表明,加权熵函数中的参数θ对关键路段排序结果影响不大,在θ=5时,该方法识别出关键路段排序结果均为路网中的问题路段(事故多发、多雨雪、高流量等),与经验情况及实际情况一致。同时,该方法还能够给出相应的路段流量分配比例,为交通规划与管理提供参考。     

论双重合约与婚姻——一个经济学的研究新框架

双重合约的内外合约就是,没有参与特定相关合约(称为内部合约)的其他人,对于内部合约产生了(外部性)影响,则上述其他人一定是同内部合约参与人达成了另外的其他合约即外部合约。双重合约是一个普遍的存在,婚姻就是其中的一种。双重合约的内、外合约既具有统一联系又存在区别。内外合约可以是排他性质不同的合约,其中一定程度内公外私性质的双重合约,是包括婚姻在内的一般组织的基本特征。根据合作博弈与讨价还价理论,可以建立双重合约下的婚姻稳定模型,其中包括合约效用、会计成本、机会成本、交易成本等重要变量。分析这些变量随社会经济条件的变化,可以解释人类婚姻规模、形式和稳定性的历史演变。