三屯营至抚宁公路唐山段路线优化研究

河北北部山区三抚公路的路线优化过程中提出了在新形势下建设新型公路、和谐公路的新理念,适当加大前期投入,确保公路使用安全,减少了后期养护费用,提高了公路的使用寿命,并为新时期的山区公路建设提出了新的看法和新的设计思路。     

福州市高速公路与三环共线段收费制式研究

对福州市区域路网进行深入调查研究,在福州市现有高速公路网收费制式的基础上,提出福州市高速公路与三环共线段多种可能的收费制式方案。对各种收费制式的交通量以及财务进行定量计算,结合定量分析结果进行综合分析和评价,确定最佳方案并评价推荐方案,归纳推荐方案存在的问题并提出相关建议。     

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.     

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。     

基于鲁棒性的船体中横剖面多目标优化

工程应用中在进行鲁棒性优化设计时,要求所求出的解既要具有较高的质量,又要满足一定的鲁棒性要求。将鲁棒性优化问题转化为一个双目标的优化问题,即一个目标为解的最优性,另一个目标为解的鲁棒性,并针对一艘最大应力接近许用应力的多用途船进行基于鲁棒性的中横剖面优化设计。首先,用支持向量机的方法建立船体舱段的近似模型,用于求取舱段的最大应力,并结合蒙特卡罗积分的思想构造出表示最大应力鲁棒性的函数;随后,以最大应力最小和最大应力的鲁棒性函数值最小为目标函数,设计出一种求解鲁棒性最优解的粒子群多目标优化算法。优化结果不仅能降低船体结构的最大应力,同时还可较大程度地提高最大应力的鲁棒性,证明了该方法的可行性。     

Two Bandwidth Packing Algorithms for the Centralized Wireless Network and Their Average-case Analysis

This paper presents a detail analysis of two bandwidth packing algorithms, used for processing connection requests in the centralized wireless network. Each call comes with a specific bandwidth request. A request can be satisfied only if there is sufficient bandwidth available during resource scheduling and allocation. Unsatisfied requests were held in a queue. The metric of bandwidth utilization ratio was used to quantify the performance of our algorithms. By theoretical analysis, our algorithms can improve the average bandwidth usage ratio significantly, about 8%~10% without adding much computation complexity. Moreover, our algorithms outperform next fit with fragmentation (NFF) algorithm when the bandwidth resource is scarce. In this paper, the contributions follows: Introducing bandwidth packing problem into wireless network; Proposing two new bandwidth packing algorithms for wireless network where the complicate scheduling algorithms are prohibited; Studying the average performance of our algorithms mathematically, which agree well with the simulation results.     

Regularization Method to the Parameter Identification of Interfacial Heat Transfer Coefficient and Properties during Casting Solidification

The accurate material physical properties, initial and boundary conditions are indispensable to the numerical simulation in the casting process, and they are related to the simulation accuracy directly. The inverse heat conduction method can be used to identify the mentioned above parameters based on the temperature measurement data. This paper presented a new inverse method according to Tikhonov regularization theory. A regularization functional was established and the regularization parameter was deduced, the Newton-Raphson iteration method was used to solve the equations. One detailed case was solved to identify the thermal conductivity and specific heat of sand mold and interfacial heat transfer coefficient (IHTC) at the meantime. This indicates that the regularization method is very efficient in decreasing the sensitivity to the temperature measurement data, overcoming the ill-posedness of the inverse heat conduction problem (IHCP) and improving the stability and accuracy of the results. As a general inverse method, it can be used to identify not only the material physical properties but also the initial and boundary conditions' parameters.     

Dynamic stability metrics for the container loading problem

The Container Loading Problem (CLP) literature has traditionally evaluated the dynamic stability of cargo by applying two metrics to box arrangements: the mean number of boxes supporting the items excluding those placed directly on the floor (M1) and the percentage of boxes with insufficient lateral support (M2). However, these metrics, that aim to be proxies for cargo stability during transportation, fail to translate real-world cargo conditions of dynamic stability.In this paper two new performance indicators are proposed to evaluate the dynamic stability of cargo arrangements: the number of fallen boxes (NFB) and the number of boxes within the Damage Boundary Curve fragility test (NB_DBC). Using 1500 solutions for well-known problem instances found in the literature, these new performance indicators are evaluated using a physics simulation tool (StableCargo), replacing the real-world transportation by a truck with a simulation of the dynamic behaviour of container loading arrangements.Two new dynamic stability metrics that can be integrated within any container loading algorithm are also proposed. The metrics are analytical models of the proposed stability performance indicators, computed by multiple linear regression. Pearson’s r correlation coefficient was used as an evaluation parameter for the performance of the models. The extensive computational results show that the proposed metrics are better proxies for dynamic stability in the CLP than the previous widely used metrics.     

Studying the benefits of carpooling in an urban area using automatic vehicle identification data

Carpooling has been considered a solution for alleviating traffic congestion and reducing air pollution in cities. However, the quantification of the benefits of large-scale carpooling in urban areas remains a challenge due to insufficient travel trajectory data. In this study, a trajectory reconstruction method is proposed to capture vehicle trajectories based on citywide license plate recognition (LPR) data. Then, the prospects of large-scale carpooling in an urban area under two scenarios, namely, all vehicle travel demands under real-time carpooling condition and commuter vehicle travel demands under long-term carpooling condition, are evaluated by solving an integer programming model based on an updated longest common subsequence (LCS) algorithm. A maximum weight non-bipartite matching algorithm is introduced to find the optimal solution for the proposed model. Finally, road network trip volume reduction and travel speed improvement are estimated to measure the traffic benefits attributed to carpooling. This study is applied to a dataset that contains millions of LPR data recorded in Langfang, China for 1 week. Results demonstrate that under the real-time carpooling condition, the total trip volumes for different carpooling comfort levels decrease by 32–49%, and the peak-hour travel speeds on most road segments increase by 5–40%. The long-term carpooling relationship among commuter vehicles can reduce commuter trips by an average of 30% and 24% in the morning and evening peak hours, respectively, during workdays. This study shows the application potential and promotes the development of this vehicle travel mode.