Improved Parallel Three-List Algorithm for the Knapsack Problem without Memory Conflicts

Based on the two-list algorithm and the parallel three-list algorithm, an improved parallel three-list algorithm for knapsack problem is proposed, in which the method of divide and conquer, and parallel merging without memory conflicts are adopted. To find a solution for the n-element knapsack problem, the proposed algorithm needs O（2^3n/8） time when O（2^3n/8） shared memory units and O（2^n/4） processors are available. The comparisons between the proposed algorithm and 10 existing algorithms show that the improved parallel three-fist algorithm is the first exclusive-read exclusive-write （EREW） parallel algorithm that can solve the knapsack instances in less than O（2^n/2） time when the available hardware resource is smaller than O（2^n/2） , and hence is an improved result over the past researches.     

规范化方法在求解狄利克莱问题中的应用

研究了在Hibert空间中求解算子方程的规范化序列方法，讨论了用规范化序列方法求解关于Poisson方程的Dirichlet问题的级数解。     

VLOOKUP函数在学生信息管理中的应用

电子表格Excel软件作为一种功能强大的数据处理工具，在高校学生管理工作中的应用日益广泛。本文以举例分析的方式探讨Excel工作表中VLOOKUP函数在学生信息管理工作中的运用，证明使用该函数在进行不同数据库的对接和交叉引用时能显著提高工作效率。     

遗传算法求解旅行商问题

本文提出一种新的遗传算法，用以求解著名的组合优化难题－旅行商问题。引用原始的文献数据，对城市数为10、30、50的试例均求得公布的最优解，对城市数为75的试例，每次结果均好于公布的最优解。用此算法求解中国旅行商问题，以20％的概率得到已知最优解1540km。或次最优解15409km，而所得最差与最好结果的相对距离为0．69％（即所得最长路径为15510km)。在COMPAQ／DX／25MH微机上每得到一个优化解平均历时150s左右。本算法与传统求解TSP问题的方法相比，具有简单、强壮、高效、高速的特点，它原则上对任何规模的对称欧几里德平面TSP具有通用性。     

Just-in-time delivery for green fleets: A feedback control approach

With increasing attention being paid to greenhouse gas (GHG) emissions, the transportation industry has become an important focus of approaches to reduce GHG emissions, especially carbon dioxide equivalent (CO₂e) emissions. In this competitive industry, of course, any new emissions reduction technique must be economically attractive and contribute to good operational performance. In this paper, a continuous-variable feedback control algorithm called GEET (Greening via Energy and Emissions in Transportation) is developed; customer deliveries are assigned to a fleet of vehicles with the objective function of Just-in-Time (JIT) delivery and fuel performance metrics akin to the vehicle routing problem with soft time windows (VRPSTW). GEET simultaneously determines vehicle routing and sets cruising speeds that can be either fixed for the entire trip or varied dynamically based on anticipated performance. Dynamic models for controlling vehicle cruising speed and departure times are proposed, and the impact of cruising speed on JIT performance and fuel performance are evaluated. Allowing GEET to vary cruising speed is found to produce an average of 12.0–16.0% better performance in fuel cost, and −36.0% to +16.0% discrepancy in the overall transportation cost as compared to the Adaptive Large Neighborhood Search (ALNS) heuristic for a set of benchmark problems. GEET offers the advantage of extremely fast computational times, which is a substantial strength, especially in a dynamic transportation environment.     

基于偏好序的高铁票价与售票时间窗联合优化

采用形式灵活且适用性好的偏好序模型刻画旅客购票选择行为，拓展现有高速铁路动态定价与售票控制策略联合优化的研究方法。按照票价变动范围划分客票等级，结合偏好序模型的特点，通过决策各等级客票售票时间窗进行售票控制，同时，在一定范围内优化各客票等级的票价，实现票价与售票控制的联合决策。本文在分析弹性客流的基础上，采用偏好序选择概率、 到达率和时间窗长度测算客票销售量。根据运营需要设定客票产品排序，以各客票产品停售时间和票价作为决策变量，建立以期望总收益最大为目标的非线性规划模型，并且将粒子群算法与线性规划精确求解嵌套求解模型。以京沪高铁为背景进行数值实验，结果表明：与固定各等级票价只优化售票时间窗的方案相比，联合优化方案可提升期望总收益约4.54%；不同需求水平下，联合优化方案的期望总收益均高于固定票价方案；期望总收益随着转移购买概率增加而增加，且不同转移概率取值下联合优化方案的期望总收益均高于固定票价方案。所提方案可为高铁列车动态定价和制定售票控制策略提供决策支持。     

基于乘客超越行为建模的航空登机效率分析

依靠缩短登机时间提升登机效率是降低航空周转成本的重要手段之一。乘客登机时间由登机策略及个体行为等因素共同决定。在采用特定登机策略登机过程中，发生阻塞导致队列行进缓慢时，队列内的乘客可能采取超越行为提升自身行进速度，从而影响登机效率。针对乘客这种超越行为建立微观仿真模型，采用元胞自动机模拟不同登机策略下的乘客登机过程，比较超越行为对不同登机策略效率的影响程度，量化考虑乘客超越行为时登机乘客携带行李比例、登机放行间隔，以及客座率等情景下登机策略的效率。结果表明：在考虑超越行为后，原本不考虑超越行为时登机时间越长策略的登机时间缩减比例越高，乘客行走干扰延误的降低是登机时间缩减的主要原因。在乘客携带行李数量较多或乘客放行间隔较短的情景下，从靠窗到过道依次登机策略的效率优于倒金字塔式策略；在客座率70%的情景下，分4种次序从后到前登机的策略是按列次序登机的最佳策略。     

基于改进社会力的单向流电动自行车行为建模研究

电动自行车作为一种便捷高效的出行工具，已在许多国家被广泛使用，但对电动自行车微观行为的研究仍十分有限。在上海海事大学对电动自行车驾驶行为进行观测实验，提取电动自行车轨迹数据，以纵向间距、速度差、侧向净距、水平间距作为特征变量，利用CART(Classification and Regression Tree)决策树分类结果建立电动自行车骑行决策行为规则。然后，基于社会力模型，分别引入超越力、跟随力等改进行为力模拟电动自行车的超越、跟随等骑行决策行为。考虑公式超越力、固定值超越力和临时目标点超越力这3种超越力形式，通过实际观测数据和仿真结果比较进行参数标定和模型验证，选取单向流电动自行车行驶场景开展数值仿真分析。结果表明：临时目标点超越力的改进社会力模型在超越过程中的轨迹误差最小，电动自行车超越时所需要的横向间距与超车时横向速度、超车完成时间成正比，最佳超车横向间距为2 m。     

Inferring patterns in the multi-week activity sequences of public transport users

The public transport networks of dense cities such as London serve passengers with widely different travel patterns. In line with the diverse lives of urban dwellers, activities and journeys are combined within days and across days in diverse sequences. From personalized customer information, to improved travel demand models, understanding this type of heterogeneity among transit users is relevant to a number of applications core to public transport agencies’ function. In this study, passenger heterogeneity is investigated based on a longitudinal representation of each user’s multi-week activity sequence derived from smart card data. We propose a methodology leveraging this representation to identify clusters of users with similar activity sequence structure. The methodology is applied to a large sample (n = 33,026) from London’s public transport network, in which each passenger is represented by a continuous 4-week activity sequence. The application reveals 11 clusters, each characterized by a distinct sequence structure. Socio-demographic information available for a small sample of users (n = 1973) is combined to smart card transactions to analyze associations between the identified patterns and demographic attributes including passenger age, occupation, household composition and income, and vehicle ownership. The analysis reveals that significant connections exist between the demographic attributes of users and activity patterns identified exclusively from fare transactions.     

Travel mode choice among same-sex couples

Same-sex partnered individuals are far more likely to use transit, walk, and cycle, and to a lesser extent, use carpools than are people in straight couples. As society becomes more tolerant, gay and lesbian populations are an increasingly visible social group, yet they have received scant attention by transportation scholars. This paper builds on this nascent literature by documenting and attempting to explain these dramatic differences by controlling for factors known to influence mode choice.We perform two separate analyses employing two distinct datasets. The first analysis examines journey-to-work data from the American Community Survey. The second analysis focuses in specifically on non-motorized (walking, biking) travel using use self-reported walk and bike frequency from the 2009 National Household Travel Survey. In both, we find that characteristics of the neighborhoods in which gays and lesbians live, as well characteristics of the individuals themselves, only explain part of the increased propensity to use “alternative” modes of transportation; a strong residual effect remains.