A note on “resource flexibility with responsive pricing”

We revisit the capacity investment decision problem studied in the article “Resource Flexibility with Responsive Pricing” by Chod and Rudi [Operations Research 53, (2005) 532–548]. A monopolist firm producing two dependent (substitutable or complementary) products needs to determine the capacity of one flexible resource under demand risk so as to maximize its expected profit. Product demands are linear functions of the prices of both products, and the market potentials are random and correlated. We perform a comparative statics analysis on how demand variability and correlation impact the optimal capacity and the resulting expected profit. In particular, C&R study this problem under the following assumptions/approximations: (i) demand intercepts follow a bivariate Normal distribution; (ii) demand uncertainty is of an additive form; (iii) and under approximate expressions for the optimal capacity and optimal expected profit. We revisit Propositions 2, 3, 4, 5, and 10 of C&R without these assumptions and approximations, and show that these results continue to hold (i) for the exact expressions for the optimal expected profit and optimal capacity, and (ii) under any arbitrary continuous distribution of demand intercepts. However, we also show that the additive demand uncertainty is a critical assumption for the C&R results to hold. In particular, we provide a case of multiplicative uncertainty under which the C&R results (Propositions 2 and 3) fail. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

基于遗传模拟退火算法的OFDMA系统资源分配

针对多用户OFDMA系统,提出了一种基于遗传模拟退火算法的多用户OFDMA系统资源分配策略。在资源分配时,首先假设总功率在载波间均等分配,随后根据比例速率要求确定每个用户需要的子带数,最后引入遗传模拟退火算法求解联合优化中的子带分配,在保证用户间公平性的前提下最大化系统吞吐量。仿真结果表明,该策略系统容量较大,并且近似满足了不同用户间传输速率比例性要求。     

动态规划在消防增援调度中的应用

由于各消防中队一般规模较小,对于较大规模的火灾需要多个消防队共同救护,此时若能够实现增援调度的最优化可以提高这些同时出现的火灾被全部扑灭的概率。利用多阶段动态规划对增援调度进行了研究,并分析了具体案例。通过分析得出此方法有助于改善消防资源分配状况,以实现最大程度地减小经济损失。     

高校资源环境类专业开设资源与环境法课程的意义

资源与环境法是高校法学类的核心课程,目前,该课程已经逐渐在资源环境类专业中不同程度的开设。高校资源环境类专业开设资源与环境法课程是非常必要而且很有意义的,（1）文章从开设资源与环境法课程有助于强化学生的环境法制教育;（2）开设资源与环境法课程有助于完善资源环境类专业的学科体系;（3）开设资源与环境法课程有利于大学生参与保护环境的实践活动;（4）开设资源与环境法课程有助于学生了解常识;（5）资源环境法课程的开设有利于丰富教学授课形式等5个方面论证了其意义性。     

支持并行工程的造船分段作业计划系统

针对传统造船模式下,车间作业计划与工艺设计串行工作方式的缺点,基于并行工程的原理,提出了分段作业计划与工艺设计的集成运行模式,为实现造船CAPP系统与PPC系统的集成化和并行化提供了实现的基础。针对集成模式的特点,建立了分段作业计划系统资源优化的数学模型,应用遗传算法解决了针对任意分段装配工艺方案的多资源平衡优化问题,可以得到每项作业最优的开工时间,同时能够给出多种资源的最优分布结果,满足了多工艺方案之间资源利用率的比较。最后,给出了计算实例,计算机模拟结果说明了这一方法的有效性。     

基于网格技术的仿真资源实时调度系统研究与实现

针对仿真资源服务运行中存在的性能瓶颈,以WSR工厂模式为基础,设计并实现了一种基于网格技术的仿真资源实时调度系统。该系统通过设置代理工厂服务,在客户端创建资源实例,实现了对仿真资源服务的实时动态调度和对资源属性的监控。原型实验证明,该系统具有调度时机合理、调度机制对服务方与客户端透明、资源监控机制不影响客户端操作和接口开放等优点。     

一种面向关键属性更新的优化数据一致性算法

规模巨大且分布性强的P2P系统可能导致部分数据副本发布的更新被长时间地延迟,从而降低Internet上资源定位的效率。针对关键属性更新的特点,提出一种解决关键属性更新冲突的优化数据一致性算法。算法中分离出用户提交的更新请求中关于关键属性的更新,在对关键更新冲突分类的基础上,采用更新缓冲预处理和关键更新表两层机制并结合最新写胜出和分而治之规则,优化关键更新冲突的发现和解决。关键属性更新的优化处理使得不会产生因为关键属性更新的延迟而降低系统基于关键属性的资源定位效率,满足面向Internet的P2P系统的要求。模拟测试结果表明该算法在一致性维护开销、资源定位开销与资源访问开销以及鲁棒性方面均具有较好的性能。     

引入价格因素的网络资源分配模型与算法实现

引入价格因素,针对网络资源分配提出PE-EMRA网络资源分配模型,并给出算法实现。PE-EMRA模型综合考虑带宽、缓冲等多种网络资源,调节并限制各业务类流量,使系统总效率最大化。该方法可有效提高资源利用率,提供服务质量保证,并具有配置灵活、实现代价小等特点。     

被动传感器融合检测系统的优化分布密度

被动传感器由于采用无源探测,而且制造成本低,体积小,在战场环境中将采用并配置大量的被动传感器来检测目标.不论是主动还是被动式传感器,在实际应用中均存在资源优化配置问题.针对被动传感器的具体应用模型,采取了若干合理近似,得到了在"OR"融合检测条件下,基于最大检测概率的被动传感器优化配置密度计算公式.     

Two-agent scheduling with linear resource-dependent processing times

This paper considers a two-agent scheduling problem with linear resource-dependent processing times, in which each agent has a set of jobs that compete with that of the other agent for the use of a common processing machine, and each agent aims to minimize the weighted number of its tardy jobs. To meet the due date requirements of the jobs of the two agents, additional amounts of a common resource, which may be in discrete or continuous quantities, can be allocated to the processing of the jobs to compress their processing durations. The actual processing time of a job is a linear function of the amount of the resource allocated to it. The objective is to determine the optimal job sequence and resource allocation strategy so as to minimize the weighted number of tardy jobs of one agent, while keeping the weighted number of tardy jobs of the other agent, and the total resource consumption cost within their respective predetermined limits. It is shown that the problem is -hard in the ordinary sense, and there does not exist a polynomial-time approximation algorithm with performance ratio unless ; however it admits a relaxed fully polynomial time approximation scheme. A proximal bundle algorithm based on Lagrangian relaxation is also presented to solve the problem approximately. To speed up convergence and produce sharp bounds, enhancement strategies including the design of a Tabu search algorithm and integration of a Lagrangian recovery heuristic into the algorithm are devised. Extensive numerical studies are conducted to assess the effectiveness and efficiency of the proposed algorithms.