Liner hub-and-spoke shipping network design

This paper proposes a liner hub-and-spoke shipping network design problem by introducing the concept of a main port, as well as some container shipping constraints such as multi-type container shipment and transit time constraints, which are seldom considered in the previous studies. It develops a mixed-integer programming model with nonconvex multi-linear terms for the proposed problem. An efficient genetic algorithm embedded with a multi-stage decomposition approach is developed to solve the model. Numerical experiments are carried out to assess the effectiveness of the proposed model and the efficiency of the proposed algorithm.     

Optimal allocation of protective resources in urban rail transit networks against intentional attacks

This paper advances the field of network interdiction analysis by introducing an application to the urban rail transit network, deploying protective resources against intentional attacks. The resource allocation problem for urban rail transit systems is considered as a game between two players, the attacker interdicting certain rail stations to generate greatest disruption impact and the system defender fortifying the network to maximize the system’s robustness to external interdictions. This paper introduces a game-theoretic approach for enhancing urban transit networks’ robustness to intentional disruptions via optimally allocating protection resources. A tri-level defender–attacker–user game-theoretic model is developed to allocate protective resources among rail stations in the rail transit network. This paper is distinguished with previous studies in that more sophisticated interdiction behaviors by the attacker, such as coordinated attack on multiple locations and various attacking intensities, are specifically considered. Besides, a more complex multi-commodity network flow model is employed to model the commuter travel pattern in the degraded rail network after interdiction. An effective nested variable neighborhood search method is devised to obtain the solution to the game in an efficient manner. A case study based on the Singapore rail transit system and actual travel demand data is finally carried out to assess the protective resources’ effectiveness against intentional attacks.     

A less-than-truckload carrier collaboration planning problem under dynamic capacities

This paper addresses the deterministic dynamic single carrier collaboration problem for the small- to medium-sized less-than-truckload (LTL) industry. It is formulated as a binary (0–1) multi-commodity minimum cost flow problem and solved using a branch-and-cut algorithm. Its inherent network structure is exploited to generate the lower bounds to the branch-and-cut algorithm using the network simplex method and by relaxing the integrality constraints. Results from numerical experiments indicate inherent trade-offs at the higher degrees of collaboration between waiting for more affordable collaborative capacity and incurring higher holding costs. They also suggest that collaborating LTL carriers experience increased capacity utilization.     

基于列生成的高速铁路车站作业计划调度调整方法研究

大型高速铁路车站到发线及列车进路的冲突是调度调整的重点,为了提高调整效率和效果,在将问题抽象为时空网络上多商品流的基础上,考虑技术作业要求、作业间隔时间、线路和进路运用规则等约束条件,以列车总晚点时间小、旅客便捷性好为目标,构建集到发线、咽喉进路和到发时刻为一体的车站作业调度调整0-1整数规划模型。针对调度调整的强实时性,设计基于列生成的求解算法,并以长春西站为例进行验证。结果表明,该方法可在较短时间内得到满意的车站作业计划调整方案。     

铁路旅客列车车底套用优化模型的研究

在列车车底数量有限的条件下,利用多商品网络流模型对列车车底的套用问题建立数学优化模型,对车底套用方案进行优化,即把列车运行图转化为网络图,而后根据流守恒、容量限制和维修等约束条件,建立以列车运输能力最大化为目标的整数规划模型。     

A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies

This paper discusses a dynamic evacuation network optimization problem that incorporates lane reversal and crossing elimination strategies. These two lane-based planning strategies complement one another by increasing capacity in specific directions through the evacuation network. A bi-level network optimization model is formulated, in which the upper level aims at optimizing the network evacuation performance subject to the lane-reversal and crossing-elimination constraints and the lower level conveys a cell transmission-based dynamic traffic assignment problem. An integrated Lagrangian relaxation and tabu search method is devised for approximating optimal problem solutions through an iterative optimization-evaluation process. The numerical results of implementing the developed modeling and solution approach to a synthetic network and a real-world example application justify its theoretical and practical value.     

Ant colony optimization for disaster relief operations

This paper presents a meta-heuristic of ant colony optimization (ACO) for solving the logistics problem arising in disaster relief activities. The logistics planning involves dispatching commodities to distribution centers in the affected areas and evacuating the wounded people to medical centers. The proposed method decomposes the original emergency logistics problem into two phases of decision making, i.e., the vehicle route construction, and the multi-commodity dispatch. The sub-problems are solved in an iterative manner. The first phase builds stochastic vehicle paths under the guidance of pheromone trails while a network flow based solver is developed in the second phase for the assignment between different types of vehicle flows and commodities. The performance of the algorithm is tested on a number of randomly generated networks and the results indicate that this algorithm performs well in terms of solution quality and run time.     

A novel hybrid-link-based container routing model

Container routing determines how to transport containers from their origins to their destinations in a liner shipping network. Container routing needs to be solved a number of times as a subproblem in tactical-level decision planning of liner shipping operations. Container routing is similar to the multi-commodity flow problem. This research proposes a novel hybrid-link-based model that nests the existing origin-link-based and destination-link-based models as special cases. Moreover, the hybrid-link-based model is at least as compact as the origin-to-destination-link-based, origin-link-based and destination-link-based models in the literature.     

A novel heuristic approach for solving aircraft landing problem with single runway

Nowadays, airlines administrations are more willing to utilize optimization tools to control air traffic due to considerable increases in volume of air transports. A challenging problem in the field of air traffic is how to optimally schedule landing time of aircrafts and assign them to different runways such that early and late landing costs are minimized. This problem is called aircraft landing problem (ALP). This paper proposes a novel decomposition based heuristic by solving two sub-problems for the ALP with single runway. In the first sub-problem, we apply the adaptive large neighborhood search (ALNS) algorithm to find a sequence of aircrafts. The solution found in the first sub-problem will be sent to the second sub-problem, to check for the feasibility of the solution using CPLEX solver. A set of benchmark problem are taken from the OR library for the purpose of comparison with other existing approaches. The computational results exhibit that the proposed algorithm is capable of finding the best known optimal solution for all the instances.     

Analysis of intermodal freight from China to Indian Ocean: A goal programming approach

This paper presents an intermodal network optimization model to examine the competitiveness of 36 alternative routings for freight moving from China to and beyond Indian Ocean. The proposed model, which is built upon the principles of goal programming, is able to handle multiple and conflicting objective functions such as minimizing transportation cost, transit time and transit time variability while ensuring flow continuity and transit nodes compatibility among the rail, road, ocean vessel, airplane and inland waterway transports. Transportation time and cost obtained from comprehensive industry sources are then fed into the intermodal transport network connecting two important Chinese origins and four Indian destinations, from which the most attractive routes are identified. In addition, the paper investigates several non-dominated transportation cases through sensitivity analysis tests, and analyzes the potential competitiveness and possible influences of future route developments to current transportation patterns in Asia.     

Global intermodal tank container management for the chemical industry

The scale of the global chemical industry is enormous: in 2003, the total value of global production exceeded US$1.7 trillion. International logistics is especially crucial to the high-value chemicals industry, since raw materials sources, production facilities, and consumer markets are distributed globally. Fluctuating demand, imbalanced trade flows, and expensive transportation equipment necessitate dynamic asset management. This paper focuses on asset management problems faced by tank container operators, and formulates an operational tank container management problem as a large-scale multi-commodity flow problem on a time-discretized network. By integrating container routing and repositioning decisions in a single model, total operating costs and fleet sizes can be reduced. A computational study verifies this hypothesis.     

Stochastic fleet deployment models for public bicycle rental systems

This paper presents two stochastic bike deployment (SBD) models that determine the optimal number of bicycles allocated to each station in a leisure-oriented public bicycle rental system with stochastic demands. The SBD models represent the stochastic demands using a set of scenarios with given probabilities. A multilayer bike-flow time-space network is constructed for developing the models, where each layer corresponds to a given demand scenario and effectively describes bicycle flows in the spatial and temporal dimensions. As a result, the models are formulated as the integer multi-commodity network flow problem, which is characterized as NP-hard. We propose a heuristic to efficiently obtain good quality solutions for large-size model instances. Test instances are generated using real data from a bicycle rental system in Taiwan to evaluate the performance of the models and the solution algorithm. The test results show that the models can help the system operator of a public bicycle system make effective fleet deployment decisions.     

Spatial-interaction network analysis of built environmental influence on daily public transport demand

Many studies have evaluated the influence of the built environment on public transport. Some studies assign subjective weights to environmental factors, which could oversimplify spatial heterogeneity and overlook the temporal dimension. On the other hand, the spatial-interaction network of public transport system is seldom considered. In this paper, we propose an improved framework to explore how individual factors unevenly affect public transport demand over space and time using a geographically and temporally weighted regression (GTWR) model. The proposed framework extends the local built environmental factors by including two network factors extracted from the spatial-interaction network of the public transport system. We conduct a case study in Beijing, China using 686 traffic analysis zones (TAZs). The actual usage of public transport, namely the public transport index (PTI), is estimated by passenger flow divided by the total amount of human flow in a given TAZ. The daily patterns of the spatial heterogeneity in some selected places in the study area is identified and analyzed. It is also found that the estimated coefficient of the variables of the spatial-interaction network is significantly larger than other static environmental factors, indicating that spatial-interaction network can more effectively reflect spatiotemporal heterogeneity in public transport demand. This study provides a better decision-making support for more accurately identifying which factors are most worthy of development, and when and where they can be implemented to improve public transit services.     

Liner shipping cargo allocation with service levels and speed optimization

The cargo allocation problem is a key strategic problem that determines the profitability of a liner shipping network. We present a novel mixed-integer programming model for this problem that introduces service levels for transit time requirements and optimizes the vessel speed on each leg of a service. These extensions to the cargo allocation problem greatly increase its realism and value for carriers. We evaluate our model on realistic data from the LINER-LIB and perform a sensitivity analysis of transit times versus bunker costs. Furthermore, we show how carriers can use our model to make data driven decisions in their operations.     

Estimating flow times for containerized imports from Asia to the United States through the Western rail network

Queuing models are introduced for estimating container dwell times at rail intermodal terminals and transit times through rail line-haul corridors. These models are statistically calibrated on industry data. The intent of these models is to estimate changes in container flow times stemming from changes in infrastructure, staffing levels at terminals, or import volumes passing through given infrastructure. Flow times estimated for individual line segments are aggregated to provide estimates of the total transit time from West Coast rail ramps to inland destination ramps for imports moving from Asia to the Continental United States in marine as well as domestic containers.     

Extending public transit accessibility models to recognise transfer location

A longstanding issue for public transit agencies has been how to assess the performance of transit service including spatial service coverage to meet the transport needs of the community. The conventional approach quantifies accessibility using door-to-door travel time in such a way that accessibility declines as the travel time to the opportunity increases. A new approach to modelling transit accessibility is proposed by incorporating the potential effect of transfer location. It builds on the premise that transit users may have a preference for a transfer location best located relative to the trip origin and destination points. The model is tested in Brisbane's bus network which has a radial form, where inner-city suburbs have relatively higher accessibility than outer-city suburbs, if only travel time is counted. Incorporating the transfer location refines the accessibility modelling so that some outer-city suburbs located along the major bus corridors have a relatively higher accessibility level. The new model also suggests that inner-city suburbs do not necessarily have better accessibility. Suburbs close to the city centre may have shorter transit travel time to reach other suburbs, but they do not have a well-connected transit network to other suburbs through service transfers.     

A heuristic approach to logistics network design for end-of-lease computer products recovery

This paper discusses the logistics network design for end-of-lease computer products recovery by developing a deterministic programming model for systematically managing forward and reverse logistics flows. Due to the complexity of such network design problem, a two-stage heuristic approach is developed to decompose the integrated design of the distribution networks into a location–allocation problem and a revised network flow problem. The applicability of the proposed method is illustrated in a numerical study. Computational experiments demonstrate that high-quality solutions are obtained while modest computational overheads are incurred.     

Optimizing road network daily maintenance operations with stochastic service and travel times

This paper studies optimization methods for a routing problem encountered in daily maintenance operations of a road network. Stochastic service and travel times on road segments are considered. The problem is formulated as a variation of the capacitated arc routing problem (CARP). A chance-constrained programming model is firstly developed and solved by a branch-and-cut algorithm. A stochastic programming model with recourse is also proposed to take into account the recourse costs in case of route failure. The problem is solved by an adaptive large neighborhood search algorithm. The computational experiments demonstrate the effectiveness of the algorithm.     

Measuring railway network performance considering accessibility levels in cities worldwide

There is a growing acceptance of and interest in transit accessibility-based developments as a means to address urban challenges, such as automobile dependency, air pollution, urban sprawl, and congestion. Additionally, prompting car drivers to switch to public transit requires the construction of attractive and accessible public transit systems. Accordingly, it is necessary to measure railway network performance while considering accessibility, which indicates the potential opportunity of interaction. Thus, this study aims to develop a railway network performance index (RPI) to evaluate transit accessibility, with regard to differences in travel speed, and conduct a comparative analysis of 40 cities worldwide. The major findings are as follows. European cities have a high RPI, but cities in developing countries have relatively low RPI values, due to railway infrastructure shortages. Railway and station density have a positive relationship with RPI, but differences in RPI emerge between cities with the same infrastructure levels. This difference indicates the importance of efficient railway system connections between the distributions of populations and facilities. Overall, this study enhances understandings of transit accessibility and provides benchmark points that may be useful for decision-making processes, transportation investments, and land use policies.     

基于EEMD-BP方法的城市轨道交通进站客流短期预测

城市轨道交通站点客流量是评价其服务水平和实现城市轨道交通资源有效配置的基础数据和依据。针对城市轨道交通站点进站客流量序列波动复杂的问题,构建基于EEMD-BP方法的城市轨道交通进站客流短期预测模型,通过对城市轨道交通站点的日间分时进站客流序列进行模态分解,并对分解的分量进行筛选和识别,探究进站客流的日间波动影响因素,实现对短期客流的合理预测。以广州珠江新城站短期客流预测为例,验证该组合模型在提高客流预测方面具有有效性,为城市轨道交通线网规划和运营管理提供客流预测依据。