加强高校财务分析的思考

文章阐述了高校财务分析的意义,分析了目前高校财务分析存在的主要问题,并就加强高校财务分析的措施进行了探讨。     

二层线性规划问题

罚函数方法是数学规划中一种常见且有效的求解方法。用罚函数原理,把二层线性规划（BLP）下层问题的对偶间隙作为惩罚项,将BLP转化为带罚函数子项的有限个线性规划问题。由于BLP的全局最优解可在约束域S的极点上找到,利用线性规划对偶理论,给出了一种求解该二层线性规划的罚函数算法。     

基于最优加权Steiner树的枢纽型物流中心选址问题

为了满足近年来物流运输业快速发展的需要,促进物流中转运输网络的合理化建设,研究了枢纽型物流中心的功能和选址原则,详细分析了影响枢纽型物流中心选址的各种因素,提出了基于结点带权的欧氏Steiner最优树的枢纽型物流中心选址方案.针对该方案设计了相应的智能优化算法,并进行了具体的程序实现.借助该方案不仅可以使总的运输成本最小,而且能够在无需事先确定备选点的数量和位置的情况下实现同时确定枢纽型物流中心的数量及位置的目标.最后以长三角地区枢纽型物流中心的建设问题为背景,对各种数据进行了仔细的分析比较,从中确定若干区域作为物流服务需求点集,并将各种因素的综合效用作为物流需求点的权值,对上述算法进行了有效性验证.     

新疆东部地区矿区资源公路建管问题的探讨

随着经济的发展和“十二五”规划的开展,新疆哈密地区成为矿产资源开发重点基地,矿区道路的质量水平决定着矿产资源的开发力度.目前,新疆哈密地区矿区资源道路的建设正处于新建、扩建和改建阶段,在建设的过程中,出现不可忽视的弊端,因此矿区资源公路的建设与管理问题成为经济发展面临的紧迫问题.如何深入分析和解决哈密矿区资源公路的弊端成为经济发展的首要问题.通过多方面细致的分析,针对弊端寻求解决方案.     

Data-driven ferry network design with candidate service arcs: the case of Zhuhai Islands in China

ABSTRACT

We investigate a ferry network design problem with candidate service arcs (FNDP-SA), which is a new variant motivated by areal-world case from Zhuhai Islands. In this research, the design of a ferry schedule must conform to strict constraints including technical feasibility, safety issues, environmental impacts and moreover, avoid conflicting with ferries from neighboring cities (i.e. HongKong, Shenzhen and Macao). Therefore, a set of cautiously approved service arcs are firstly given, based on which the ferry service network is optimized. This study is among the first to formally describe the FNDP-SA and model it as an integer program. A hybrid variable neighborhood descent (VND)-based algorithm is developed. Two sets of instances are generated based on the case of Zhuhai Islands, where the first set is based on historical ticket sales data while the second set is derived by incorporating increased demands in the future according to a questionnaire survey. Numerical studies have shown that 59% cost reduction on the first set can be achieved by the proposed VND algorithm when compared with manual results. Research outcomes of this study have been adopted and implemented to facilitate the sustainable development of the ferry service of Zhuhai Islands.     

Distance-dependent congestion pricing for downtown zones

A growing literature exploits macroscopic theories of traffic to model congestion pricing policies in downtown zones. This study introduces trip length heterogeneity into this analysis and proposes a usage-based, time-varying congestion toll that alleviates congestion while prioritizing shorter trips. Unlike conventional trip-based tolls the scheme is intended to align the fees paid by drivers with the actual congestion damage they do, and to increase the toll’s benefits as a result.The scheme is intended to maximize the number of people that finish their trips close to their desired times. The usage-based toll is compared to a traditional, trip-based toll which neglects trip length. It is found that, like trip-based tolls, properly designed usage-based tolls alleviate congestion. But they reduce schedule delay more than trip-based tolls and do so with much smaller user fees. As a result usage-based tolls leave most of those who pay with a large welfare gain. This may increase the tolls’ political acceptability.     

The split-demand one-commodity pickup-and-delivery travelling salesman problem

This paper introduces a new vehicle routing problem transferring one commodity between customers with a capacitated vehicle that can visit a customer more than once, although a maximum number of visits must be respected. It generalizes the capacitated vehicle routing problem with split demands and some other variants recently addressed in the literature. We model the problem with a single commodity flow formulation and design a branch-and-cut approach to solve it. We make use of Benders Decomposition to project out the flow variables from the formulation. Inequalities to strengthen the linear programming relaxation are also presented and separated within the approach. Extensive computational results illustrate the performance of the approach on benchmark instances from the literature.     

A distributed VNS algorithm for optimizing dial-a-ride problems in large-scale scenarios

These days, transportation and logistic problems in large cities are demanding smarter transportation services that provide flexibility and adaptability. A possible solution to this arising problem is to compute the best routes for each new scenario. In this problem, known in the literature as the dial-a-ride problem, a number of passengers are transported between pickup and delivery locations trying to minimize the routing costs while respecting a set of prespecified constraints. This problem has been solved in the literature with several approaches from small to medium sized problems. However, few efforts have dealt with large scale problems very common in massive scenarios (big cities or highly-populated regions). In this study, a new distributed algorithm based on the partition of the requests space and the combination of the routes is presented and tested on a set of 24 different scenarios of a large-scale problem (up to 16,000 requests or 32,000 locations) in the city of San Francisco. The results show that, not only the distributed algorithm is able to solve large problem instances that the corresponding sequential algorithm is unable to solve in a reasonable time, but also to have an average improvement of 9% in the smaller problems. The results have been validated by means of statistical procedures proving that the distributed algorithm can be an effective way to solve high dimensional dial-a-ride problems.     

The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery

Once limited to the military domain, unmanned aerial vehicles are now poised to gain widespread adoption in the commercial sector. One such application is to deploy these aircraft, also known as drones, for last-mile delivery in logistics operations. While significant research efforts are underway to improve the technology required to enable delivery by drone, less attention has been focused on the operational challenges associated with leveraging this technology. This paper provides two mathematical programming models aimed at optimal routing and scheduling of unmanned aircraft, and delivery trucks, in this new paradigm of parcel delivery. In particular, a unique variant of the classical vehicle routing problem is introduced, motivated by a scenario in which an unmanned aerial vehicle works in collaboration with a traditional delivery truck to distribute parcels. We present mixed integer linear programming formulations for two delivery-by-drone problems, along with two simple, yet effective, heuristic solution approaches to solve problems of practical size. Solutions to these problems will facilitate the adoption of unmanned aircraft for last-mile delivery. Such a delivery system is expected to provide faster receipt of customer orders at less cost to the distributor and with reduced environmental impacts. A numerical analysis demonstrates the effectiveness of the heuristics and investigates the tradeoffs between using drones with faster flight speeds versus longer endurance.     

基于工效学的机车显示、控制器界面计算机辅助优化设计

应用优化匹配(CSP)技术,根据操作任务、功能和工效学要求,在机车操纵显示和控制单元之间建立约束条件,构造目标函数,进行优化计算。论文对CSP模型进行了改进,提出了一种适用于多面板显示、控制器界面的计算机辅助设计方法,并有效地对机车多面板显示、控制器界面进行了优化设计,在我国铁路机车司机室规范化设计工作中得到了较好的应用。