An optimal data-splitting algorithm for aircraft scheduling on a single runway to maximize throughput

In this research, we present a data-splitting algorithm to optimally solve the aircraft sequencing problem (ASP) on a single runway under both segregated and mixed-mode of operation. This problem is formulated as a 0–1 mixed-integer program (MIP), taking into account several realistic constraints, including safety separation standards, wide time-windows, and constrained position shifting, with the objective of maximizing the total throughput. Varied scenarios of large scale realistic instances of this problem, which is NP-hard in general, are computationally difficult to solve with the direct use of commercial solver as well as existing state-of-the-art dynamic programming method. The design of the algorithm is based on a recently introduced data-splitting algorithm which uses the divide-and-conquer paradigm, wherein the given set of flights is divided into several disjoint subsets, each of which is optimized using 0–1 MIP while ensuring the optimality of the entire set. Computational results show that the difficult instances can be solved in real-time and the solution is efficient in comparison to the commercial solver and dynamic programming, using both sequential, as well as parallel, implementation of this pleasingly parallel algorithm.     

Foldable container in empty container repositioning in intermodal transportation network of Belt and Road Initiative: strengths and limitations

In 2013, the concept of the ‘Silk Road Economic Belt and the 21st-Century Maritime Silk Road (Belt and Road)’ was initiated by the Chinese government, which involves Asian, European and African continents and their adjacent seas. Logistics plays a core role in such a large framework of economy and trade. In recent years, China, European Union, and Southeast Asia pay much attention to the design and development of the intermodal transportation network towards both economic and environmental efficiency. In this paper, we propose an empty container repositioning model in the intermodal transportation network of Belt and Road (B&R) Initiative by considering both standard and foldable containers. In this model, empty containers are repositioned from the inland of the original area, such as China, to other areas of B&R Initiative related countries and regions, such as European Union and Southeast Asia. We develop a mixed integer linear programming model to determine the optimal repositioning of empty containers via the intermodal transportation network. An Artificial Bee Colony algorithm is developed to solve large size problems in practice and numerical experiments are conducted to show the efficiency of our proposed algorithm. We provide managerial insights regarding the impact on the network performance of foldable containers transportation.     

Direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem

This paper proposes simple and direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem. It is only necessary to account for random variables independent of link flows by performing a simple transformation of the perceived link travel time with a normal distribution. At every iteration of a Monte-Carlo simulation procedure, the values of the random variables are sampled based on their probability distributions, and then a regular deterministic user equilibrium assignment is carried out to produce link flows. The link flows produced at each iteration of the Monte-Carlo simulation are averaged to yield the final flow pattern. Two test networks demonstrate that the proposed algorithms and the traditional algorithm (the Method of Successive Averages) produce similar results and that the proposed algorithms can be extended to the computation of the case in which the random error term depends on measured travel time.     

基于AIGA-WLSSVM的埋地管道腐蚀速率预测方法

为了降低埋地管道腐蚀影响因素之间的复杂相关性,提高腐蚀预测精度,文中提出一种基于自适应免疫遗传算法-加权最小二乘支持向量机(AIGA-WLSSVM)的埋地管道腐蚀速率预测建模方法,并采用AIGA优化模型参数,进一步提高模型的学习能力和稳定性。最后通过实例分析验证了AIGA-WLSSVM建模方法在埋地管道腐蚀速率预测中的可行性和有效性,为埋地管道的检修与更换提供参考。     

VTS中雷达信息与AIS信息融合的探讨

文章对VTS中雷达信息与AIS信息的来源、种类与特点进行了比较,论证了两者信息融合的可行性与必要性,同时给出了信息的融合模型与方法,也提出信息融合需要进一步解决的问题.     

A two-phase model for dry port location with an application to the port of Dalian in China

This paper provides guidance for an optimal and reasonable dry port layout for the port of Dalian in China. We present a two-phase framework on the location of dry ports, which solves the selection of candidate inland cities and optimal dry port location choice, respectively. Fuzzy C-Means Clustering is applied to select alternative cities in the vast hinterland of the seaport of Dalian, with a view to identify evaluation factors that affect the location selection decision. A cost-minimisation linear programming solution is proposed, with the aid of a genetic algorithm, to choose the optimal location as well as capacity level among the candidate inland cities.     

Dynamic demand estimation and prediction for traffic urban networks adopting new data sources

Nowadays, new mobility information can be derived from advanced traffic surveillance systems that collect updated traffic measurements, both in fixed locations and over specific corridors or paths. Such recent technological developments point to challenging and promising opportunities that academics and practitioners have only partially explored so far.The paper looks at some of these opportunities within the Dynamic Demand Estimation problem (DDEP). At first, data heterogeneity, accounting for different sets of data providing a wide spatial coverage, has been investigated for the benefit of off-line demand estimation. In an attempt to mimic the current urban networks monitoring, examples of complex real case applications are being reported where route travel times and route choice probabilities from probe vehicles are exploited together with common link traffic measurements.Subsequently, on-line detection of non-recurrent conditions is being recorded, adopting a sequential approach based on an extension of the Kalman Filter theory called Local Ensemble Transformed Kalman Filter (LETKF).Both the off-line and the on-line investigations adopt a simulation approach capable of capturing the highly nonlinear dependence between the travel demand and the traffic measurements through the use of dynamic traffic assignment models. Consequently, the possibility of using collected traffic information is enhanced, thus overcoming most of the limitations of current DDEP approaches found in the literature.     

基于环境风险控制的危险废物选址-路径问题研究

为降低回收处理危险废物的环境危害,提出了基于环境风险控制的危险废物选址-路径问题,全面地评估了危险废物回收管理的环境风险.根据环境承载力的理论,设计了环境风险的度量方法.考虑废物残余的危险性、危险废物类型和加工技术种类的多样性、危险废物和加工技术的相容性,建立了成本最小化和环境风险最小化的0-1混合整数线性规划模型.针对双目标选址-路径模型的复杂性特点,设计了多阶段聚类遗传算法.以重庆危险废物物流管理为例,验证了模型和算法的有效性.结果表明:模型和算法能够为实际管理提供合理的选址-路径优化方案,且在两个不同对比条件下,相较于已有的模型,基于环境风险控制的优化方案能够分别降低33.85％和18.16％的总成本.     

多模式区域公交协调调度模型和算法

考虑公交内部及公交和地铁、长途客运之间的换乘衔接问题,满足最小和最大发车间隔等现实约束因素,建立了一类多目标多模式公交协调时刻表模型,在某时段内分别追求非换乘和换乘出行者在所有站点的等车时间最少和所有车辆到达站点时的泊位数最多.利用约束法将该问题转化为单目标规划问题.根据模型特征,设计求解该问题的改进细菌觅食优化算法,定义解的编码方案,设计产生初始种群的启发式算法,将梯度概念引入移动步长进而改进细菌觅食操作.最后,结合一个简单算例,比较单模式和多模式区域公交协调调度之间的差异,分析了站点通行能力对调度结果的影响,并将该算法与其他智能算法进行了比较分析,从而验证了模型和算法的正确性和有效性.     

基于多目标遗传算法的约束阻尼柱壳结构优化

文章为了改进被动约束阻尼柱壳结构的减振特性,解决引入约束阻尼的合理分布问题,提出了一种基于多目标遗传算法的优化设计方法。建立了以振动模态的前两阶损耗因子和引入约束阻尼材料总质量比为优化目标,以约束层、阻尼层厚度和粘弹性材料剪切模量为设计变量的多目标函数。利用遗传算法对 Pareto 最优进行优化选择,避免了对目标函数值的直接计算。通过分析和比较优化前后结构的模态振动频率变化以及幅频响应,表明引入质量太多会影响柱壳结构固有特性,而优化后结构能够避免太多的质量引入,并且具有更好的减振效果。