浅谈直接空冷机组乏汽余热利用改造后的安全运行

汽轮机乏汽余热利用是目前火力发电厂节能降耗,增加供热面积的一项重要工程,本文结合我厂实际对乏汽余热利用改造工程的优化进行了介绍,对热泵投运过程中及投运后对机组安全运行的影响和采取的措施进行了总结。     

土建工程现场管理优化策略分析

本文在分析目前土建工程现场管理主要内容及所存在问题的基础上,对优化土建工程现场管理提出合理化建议。     

对体育比赛场馆项目流程管理的若干思考

该文章在简要介绍流程管理的定义后,引出体育比赛场馆项目流程管理的相关定义,进而分析阐明了体育比赛场馆建设项目流程管理的现状,并对当前市场上存在的流程管理方面的问题进行了论述,最后针对这些问题提出一系列相应的优化措施,为体育比赛场馆建设项目的流程管理提供了借鉴。     

优化生产环节和劳动组织管理提高掘进单进水平

本文介绍了双马煤矿的建设情况,对矿井建设过程中制约掘进单进水平的原因进行了分析,提出优化生产环节、改进施工工艺和优化劳动组织管理、提高劳动工效的具体措施。     

基于改进粒子群算法的无人机航迹规划

针对当前基本粒子群算法无人机航迹规划在后期收敛速度比较慢、效率不高、易陷入局部最优等问题,提出一种改进粒子群算法。首先,在迭代前期和后期分段设置惯性权值的调整,实现粒子惯性和寻优行为的平衡;其次,设置一个定值与相邻2次适应度函数最优值比较策略,防止陷入局部最优;最后,引入遗传算法的交叉、变异机制,得出更优的结果。并通过仿真验证了改进粒子群算法在三维空间航迹规划的有效性和可行性。结果表明,与其他航迹规划算法相比,新算法具有路径长度更短、耗时更少、路径更平滑等优点,加快了收敛速度,提高了航迹规划效率和稳定性。因此,改进算法的航迹规划可得到满足约束关系的最优航迹,对实现自主飞行有重要的参考价值。     

Optimal granularity for portfolio choice

Many optimization-based portfolio rules fail to beat the simple 1/N rule out-of-sample because of parameter uncertainty. In this paper we suggest a grouping strategy in which we first form groups of equally weighted stocks and then optimize over the resulting groups only. This strategy aims at balancing the trade-off between the benefits from optimization and the losses from estimation risk. We rely on Monte-Carlo simulations to illustrate the performance of the strategy, and we derive the optimal group size for a simplified setup. Furthermore, we show that estimation risk also has an impact via the criterion by which the assets are sorted into groups (like the expected excess returns or betas), but does not negate the grouping approach. We relate our work to linear asset pricing models, and we conduct out of sample back-tests in order to confirm the validity of our grouping strategy empirically.     

耕地利用多功能权衡关系测度与分区优化 ——以河南省为例

研究目的:分析河南省耕地利用多功能空间分布特征、多功能权衡关系区域差异,提出分区优化管控措施。研究方法:耦合协调度方法、权衡强度方法。研究结果:(1)河南省各县(区)耕地利用多功能呈现明显的空间异质性,中原城市群生产功能和社会保障功能优势明显,黄淮平原生产—生态功能强;(2)多功能协调度、权衡强度空间差异明显,中原城市群和豫北地区协调程度高、权衡强度低;(3)全省可耕地划分为多功能高协调区、多功能低协调区、单功能主导区、生产—生态协调区、生产—社会保障协调区、生态—社会保障协调区6大区域。研究结论:研究结果与河南省区域发展战略定位相符,揭示河南省耕地利用多功能分布和权衡关系,划分不同类型区并提出优化建议,为河南省农业空间管控提供决策支持。     

Stochastic regularization for the mean-variance allocation scheme

Despite being based on sound principles, the original Markovitz portfolio allocation theory cannot produce sound allocations, and restrictions or modifications need to be imposed from outside the theory in order to obtain meaningful portfolios. This is unsatisfactory, and the reasons for this failure are discussed, in particular, the unavoidable small eigenvalues of the covariance. Within the original principles of risk minimization and return maximization, several modifications of the original theory are introduced. First, the strategic and tactical time horizons are separated. A base long-term allocation is chosen at the strategic time horizon, while the portfolio is optimized at the tactical time horizon using information from the price histories. Second, the tactical portfolio is financed by the strategic one, and a funding operator is introduced. The corresponding optimal allocation (without constraints) has one free parameter fixing the leverage. Third, the transaction costs are taken into account. This includes the current re-allocation cost, but crucially the expected costs of the next reallocation. This last term depends on the sensitivity of the allocation with respect to the covariance, and the expectation introduces another dependency on the (inverse) covariance. The new term regularizes the original minimization problem by modifying the lower part of the spectrum of the covariance, leading to meaningful portfolios. Without constraints, the final Lagrangian can be minimized analytically, with a solution that has a structure similar to the original Markovitz solution, but with the inverse covariance regularized by the expected transaction costs.     

Pareto efficient allocation of an in-motion wireless charging infrastructure for electric vehicles in a multipath network

Electric vehicles (EV) use an eco-friendly technology that limits the greenhouse gas emissions of the transport sector, but the limited battery capacity and the density of the battery are the major barriers to the widespread adoption of EV. To mitigate this, a good method seems to be the innovative wireless charging technology called ‘On-Line EV (OLEV)’, which is a contactless electric power transfer technology. This EV technology has the potential to charge the vehicle’s battery dynamically while the vehicle is in motion. This system helps to reduce not only the size of the battery but also its cost, and it also contributes to extending the driving range before the EV has to stop. The high cost of this technology requires an optimal location of the infrastructure along the route. For this reason, the objective of this paper is to study the problem of the location of the wireless charging infrastructure in a transport network composed of multiple routes between the origin and the destination. To find a strategic solution to this problem, we first and foremost propose a nonlinear integer programming solution to reach a compromise between the cost of the battery, which is related to its capacity, and the cost of installing the power transmitters, while maintaining the quality of the vehicle’s routing. Second, we adapt the multi-objective particle swarm optimization (MPSO) approach to our problem, as the particles were robust in solving nonlinear optimization problems. Since we have a multi-objective problem with two binary variables, we combine the binary and discrete versions of the particle swarm optimization approach with the multi-objective one. The port of Le Havre is presented as a case study to illustrate the proposed methodology. The results are analyzed and discussed in order to point out the efficiency of our resolution method.     

Spatial determinants of productivity growth on agri‐food Spanish firms: a comparison between cooperatives and investor‐owned firms

This study analyses the effect of the spatial factor, location, and interaction effects among peer companies, on the productivity growth of agri‐food companies in Spain. With this aim, we build a productivity growth index and apply a multiequational Seemingly Unrelated Regression on a sample of 344 Spanish cooperatives and investor‐owned firms for the period 2010–2012. Our findings show that agri‐food firms are influenced by spatial factors finding interesting differences between cooperatives and investor‐owned firms. With regard to the geographical location, cooperatives in the western of Spain show higher productivity growth rates, whereas investor‐owned firms in the northeast of Spain present better results. The interaction effect among closer peer companies is also a relevant factor to determine the productivity growth in agri‐food companies. This factor is more relevant for cooperatives than for investor‐owned firms.