Order-first split-second methods for vehicle routing problems: A review

Cluster-first route-second methods like the sweep heuristic (Gillett and Miller, 1974) are well known in vehicle routing. They determine clusters of customers compatible with vehicle capacity and solve a traveling salesman problem for each cluster. The opposite approach, called route-first cluster-second, builds a giant tour covering all customers and splits it into feasible trips. Cited as a curiosity for a long time but lacking numerical evaluation, this technique has nevertheless led to successful metaheuristics for various vehicle routing problems in the last decade. As many implementations consider an ordering of customers instead of building a giant tour, we propose in this paper the more general name of ordering-first split-second methods. This article shows how this approach can be declined for different vehicle routing problems and reviews the associated literature, with more than 70 references.     

Multi-objective optimization of train routing problem combined with train scheduling on a high-speed railway network

Based on train scheduling, this paper puts forward a multi-objective optimization model for train routing on high-speed railway network, which can offer an important reference for train plan to provide a better service. The model does not only consider the average travel time of trains, but also take the energy consumption and the user satisfaction into account. Based on this model, an improved GA is designed to solve the train routing problem. The simulation results demonstrate that the accurate algorithm is suitable for a small-scale network, while the improved genetic algorithm based on train control (GATC) applies to a large-scale network. Finally, a sensitivity analysis of the parameters is performed to obtain the ideal parameters; a perturbation analysis shows that the proposed method can quickly handle the train disturbance.     

A hybrid optimization-simulation approach for robust weekly aircraft routing and retiming

We address the robust weekly aircraft routing and retiming problem, which requires determining weekly schedules for a heterogeneous fleet that maximizes the aircraft on-time performance, minimizes the total delay, and minimizes the number of delayed passengers. The fleet is required to serve a set of flights having known departure time windows while satisfying maintenance constraints. All flights are subject to random delays that may propagate through the network. We propose to solve this problem using a hybrid optimization-simulation approach based on a novel mixed-integer nonlinear programming model for the robust weekly aircraft maintenance routing problem. For this model, we provide an equivalent mixed-integer linear programming formulation that can be solved using a commercial solver. Furthermore, we describe a Monte-Carlo-based procedure for sequentially adjusting the flight departure times. We perform an extensive computational study using instances obtained from a major international airline, having up to 3387 flights and 164 aircraft, which demonstrates the efficacy of the proposed approach. Using the simulation software SimAir to assess the robustness of the solutions produced by our approach in comparison with that for the original solutions implemented by the airline, we found that on-time performance was improved by 9.8–16.0%, cumulative delay was reduced by 25.4–33.1%, and the number of delayed passengers was reduced by 8.2–51.6%.     

桩基施工中的常见问题解析

该文分析了施工中常见的两种桩基易出现的问题及原因,并结合广州西二环高速公路某特大桥桩基工程实例,从混凝土质量、夹泥断桩、导管进水等方面进行了分析总结。     

利用改进交叉算子的混合遗传算法求解VRPTW

设计了一种改进的混合遗传算法求解带有时间窗、有车辆重量限制的车辆优化调度问题（VRPTW），根据问题的实际情况，建立了数学模型，提出了改进的交叉算子，丰富了种群的多样性；并结合模拟退火算法的思想，对染色体的适应度适当变化，改善了传统的遗传算法容易“早熟”的缺点，加强了染色体的局部搜索能力。     

具有同时配送和回收需求的车辆路径问题的混合遗传算法

介绍了具有同时配送和回收需求的车辆路径问题(VRPSDP),并对其进行了描述,建立了该问题的数学规划模型。结合2-opt法和等级替换策略等设计了求解VRPSDP的一种混合遗传算法,给出了该算法初始种群的两种生成规则———随机生成和构造初始种群,设计了相应的交叉和变异算子,并详细阐述了违反约束条件的处理方法。通过随机模拟试验以及与其他方法的对比分析表明:该算法可有效缩短车辆行驶距离,而构造初始种群则在一定条件下可显著提高混合遗传算法的收敛速度并改善其运行结果。     

Ant Colony Routing algorithm for freeway networks

Dynamic traffic routing refers to the process of (re)directing vehicles at junctions in a traffic network according to the evolving traffic conditions. The traffic management center can determine desired routes for drivers in order to optimize the performance of the traffic network by dynamic traffic routing. However, a traffic network may have thousands of links and nodes, resulting in a large-scale and computationally complex non-linear, non-convex optimization problem. To solve this problem, Ant Colony Optimization (ACO) is chosen as the optimization method in this paper because of its powerful optimization heuristic for combinatorial optimization problems. ACO is implemented online to determine the control signal – i.e., the splitting rates at each node. However, using standard ACO for traffic routing is characterized by four main disadvantages: 1. traffic flows for different origins and destinations cannot be distinguished; 2. all ants may converge to one route, causing congestion; 3. constraints cannot be taken into account; and 4. neither can dynamic link costs. These problems are addressed by adopting a novel ACO algorithm with stench pheromone and with colored ants, called Ant Colony Routing (ACR). Using the stench pheromone, the ACR algorithm can distribute the vehicles over the traffic network with less or no traffic congestion, as well as reduce the number of vehicles near some sensitive zones, such as hospitals and schools. With colored ants, the traffic flows for multiple origins and destinations can be represented. The proposed approach is also implemented in a simulation-based case study in the Walcheren area, the Netherlands, illustrating the effectiveness of the approach.     

Intermodal and international freight network modeling

The authors describe the development and application of a single, integrated digital representation of a multimodal and transcontinental freight transportation network. The network was constructed to support the simulation of some five million origin to destination freight shipments reported as part of the 1997 United States Commodity Flow Survey. The paper focuses on the routing of the tens of thousands of intermodal freight movements reported in this survey. Routings involve different combinations of truck, rail and water transportation. Geographic information systems (GIS) technology was invaluable in the cost-effective construction and maintenance of this network and in the subsequent validation of mode sequences and route selections. However, computationally efficient routing of intermodal freight shipments was found to be most efficiently accomplished outside the GIS. Selection of appropriate intermodal routes required procedures for linking freight origins and destinations to the transportation network, procedures for modeling intermodal terminal transfers and inter-carrier interlining practices, and a procedure for generating multimodal impedance functions to reflect the relative costs of alternative, survey reported mode sequences.     

轮胎压路机驱动方式的对比分析

通过对现有市场上的轮胎压路机机械传动、液力传动、液压传动3种传动方式的对比分析，归纳出其优缺点，综合分析得出液压传动的轮胎压路机在性能、工作效率、维护保养、驾驶的舒适性方面有着较为明显的优势。     

Wave and sea level monitoring and prediction in the service module of the Global Ocean Observing System (GOOS)

The need for a Global Ocean Observing System Global (GOOS) is now widely appreciated. Parts of GOOS are currently being implemented already. In this paper, written on the request of the joint Scientific and Technical Committee of GOOS, we present some of the scientific issues that need to be addressed for the further development of the Ocean and Marine Meteorology Service module of GOOS. This module is concerned with monitoring and prediction of sea level (both tsunamis and storm surges) and wind driven waves (wind–sea and swell), among other things. For each of these we discuss the current state-of-the-art, indicate what observations are needed and make suggestions for future modelling development.