A strategic model of port-hinterland freight distribution networks

This paper presents a strategic model for port-hinterland freight distribution networks. The approach utilizes a combination of a multi-objective optimization model to estimate locations and networks of distribution centers and an assignment model that recognizes distributed service level preferences. Our example application concerns the European continent and is transferable to other regions. The model calibration is able to explain the European port-hinterland distribution structures satisfactorily. We compute novel performance measures that take into account port-hinterland distribution structures. The measures include port-hinterland transport cost, port-hinterland transport time, and distribution center-hinterland transport time. These measures can provide inputs for port-connectivity studies.     

Optimal vendor selection in a multiproduct supply chain with truckload discounts

When products are sold by multiple vendors in various locations, the purchaser must decide what to order from each vendor and where to send it. To solve this decision problem, a novel optimization model is developed and applied to a situation involving the nationwide wholesale distribution of grocery products. Comparing the model’s solution with the actual record of shipments reveals instances in which the model selected higher-priced vendors in order to capitalize on truckload cost savings, which are seen to be an important factor in vendor selection. Additional models are developed to reduce computation time and assign shipments to vehicles.     

A three-stage stochastic facility routing model for disaster response planning

This paper presents a three-stage mixed-integer stochastic programming model for disaster response planning, considering the opening of local distribution facilities, initial allocation of supplies, and last mile distribution of aid. The vehicles available for transportation, the state of the infrastructure and the demand of the potential beneficiaries are considered as stochastic elements. Extensive computational testing performed on realistic instances shows that the solutions produced by the stochastic programming model are significantly better than those produced by a deterministic expected value approach.     

A metaheuristic approach to the reliable location routing problem under disruptions

This paper examines a reliable capacitated location–routing problem in which depots are randomly disrupted. Customers whose depots fail must be reinserted into the routes of surviving depots. We present a scenario-based mixed-integer programming model to optimize depot location, outbound delivery routing, and backup plans. We design a metaheuristic algorithm that is based on a maximum-likelihood sampling method, route-reallocation improvement, two-stage neighborhood search and simulated annealing. Numerical tests show that the heuristic is able to generate results that would keep operating costs and failure costs well balanced. Managerial insights on scenario identification, facility deployment and model simplification are drawn.     

A reactive tabu search algorithm for the multi-depot container truck transportation problem

A container truck transportation problem that involves multiple depots with time windows at both origins and destinations, including the reposition of empty containers, is formulated as a multi-traveling salesman problem with time windows (m-TSPTW) with multiple depots. Since the problem is NP-hard, a cluster method and a reactive tabu search (RTS) algorithm are developed to solve the problem. The two methods are compared with the mixed integer program which can be used to find optimum solutions for small size problems. The computational results show that the developed methods, particularly the RTS algorithm, can be efficiently used to solve the problem.     

Urban public charging station locating method for electric vehicles based on land use approach

Since the use of electric vehicles decreases the local pollution and noise emission electromobility gains a huge potential in sustainable transport. The currently insufficient charging network, namely the low number of stations and ill-chosen locations are a significant barrier of the widespread of electric vehicles in many countries. Accordingly, localization of new charging stations is of utmost importance. In this study, we develop a two-level charging station locating method. Weighted multicriteria methods were introduced to evaluate territory segments and allocate charging stations within a segment applying a hexagon-based approach and using a greedy algorithm. The novelty of the method in comparison with previous studies is that it assesses the potential of electric vehicle use on macro-level and the possible locations of charging stations on micro-level with a focus on the land-use. We apply the method to Hungary (macro evaluation) and to a district of the capital city, Budapest (micro evaluation). It is found that charging stations at P + R facilities, close to concentrated services and high-density areas are better suited to serve urban public charging demand than gas stations.     

Demand for environmentally friendly vehicles: A review and new evidence

Although the need for more environmentally friendly vehicles was recognized some decades ago, this new market has not yet established itself. Consumer behavior needs to be studied to ascertain when people will decide to purchase hybrid or electric vehicles rather than conventional ones. An in-depth review of the state-of-the-art has identified existing deficiencies and these are addressed in this paper, proposing a new approach that is applied to the case of Santander in Spain. Emphasis is placed on the role of citizens in researching the local market and their requirements with respect to such vehicles; our model assumes variability in user preferences, an utmost requirement as concluded from the literature review. Results suggest that the highest demand for cleaner vehicles would be achieved in two ways: firstly, by penalizing conventional vehicles in terms of costs/km; secondly, by providing incentives directed at lowering the purchasing price of hybrid and electric vehicles. Finally, as demand becomes more elastic, the preferred strategy should initially focus on hybrid vehicles.     

Local distribution and collection for environmental and social sustainability – tricycles in central Beijing

Goods distribution is a growing proportion of intra-urban transport worldwide due to changes in supply chains and e-commerce, yet has received scant attention in research. Cities have opted for a regulatory approach to truck movement and deliveries at a local level but few have tried to develop a systematic approach to management. Following certain suggestions in the literature, a hierarchical deliveries approach is being adopted in some new developments in Europe and Australia using light vehicles at the local level. In East, South and South-East Asia, where 3-wheeled non-motorised vehicles have been a mainstay of goods and people transport for several decades, they are under renewed pressure from city governments. This study of the tricycle in Beijing examines their role for packages delivery, food and beverage distribution and waste and recycling services, which covers nearly all of the uses of utilitarian tricycles in northern Chinese cities. Drivers (n = 97) were interviewed, their usual trips were mapped, and the subsequent trip was recorded using a geo-positioning system. These trips were compared with trips executed by small, motorised vans, favoured since 2014 by Beijing government. Operations can be divided into four categories according to delivery chain organisation, field operations and vehicle type. Motorised alternatives to the tricycle are shown to be uncompetitive in terms of time, cost and energy efficiency. This first detailed examination of the operations of the tricycle in a Chinese city provides a useful base for consideration of local distribution services organisation and a possible model for cities outside China.     

The effect of a roundabout corridor's design on selecting the optimal crosswalk location: A multi-objective impact analysis

Crosswalks located at mid-block segment between roundabouts can provide a good balance among delay, carbon dioxide (CO₂) emissions, and relative difference between vehicles and pedestrians speed. However, when considering local pollutant criteria, the optimal crosswalk location may be different to that obtained for CO₂. This paper described a multi-objective analysis of pedestrian crosswalk locations, with the objectives of minimizing delay, emissions, and relative difference between vehicles and pedestrians speed. Accounting for the difference between global (e.g., CO₂) and local pollutants (monoxide carbon, nitrogen oxides, and hydrocarbons) was one the main considerations of this work. Vehicle activity along with traffic and pedestrian flows data at six roundabout corridors in Portugal, one in Spain, and one in the United States were collected and extracted. A simulation environment using VISSIM, Vehicle Specific Power, and Surrogate Safety Assessment Model models was used to evaluate traffic operations along the sites. The Fast Non-Dominated Sorting Genetic Algorithm (NSGA-II) was implemented to further search optimal crosswalk locations. The results yielded improvements to both delay and emissions by using site-optimized crosswalks. The findings also revealed that the spacing between intersections widely influenced the optimal crosswalk location along a mid-block section. If the spacing is low (<100 m), the crosswalk location will be approximately in 20%–30% of the spacing length. For spacing values between 140 and 200 m, crosswalks would be located at the midway position. When a specific pollutant criterion was considered, no significant differences were observed among optimal crosswalk data sets.     

Infrastructure development for alternative fuel vehicles on a highway road system

A new mathematical model for positioning alternative fuel (AF) refueling stations on directed-transportation networks with the objective of maximizing the coverage of path flow volume is proposed. This model is especially designed for developing an AF infrastructure on toll roads and other highways, where vehicles do not need to exit the road network for refueling, some candidate station locations are not located at interchanges, and some stations may only service vehicles on one driving direction. The proposed model is applied to the Pennsylvania Turnpike System using the 2011 truck traffic data and considering different vehicle driving ranges.     

Real-time relief distribution in the aftermath of disasters – A rolling horizon approach

This paper presents a rolling horizon-based framework for real-time relief distribution in the aftermath of disasters. This framework consists of two modules. One is a state estimation and prediction module, which predicts relief demands and delivery times. The other is a relief distribution module, which solves for optimal relief distribution flows. The goal is to minimize the total time to deliver relief goods to satisfy the demand, considering uncertain data and of the risk-averse attitude of the decision-maker. A numerical example based on the large-scale earthquake that occurred on September 21, 1999 in Taiwan is presented to demonstrate the system.     

A two-echelon inventory allocation and distribution center location analysis

The optimization of locations for distribution centers is influenced by the demand for individual products. Lower demand products are often more effectively held in more centralized locations than higher demand products. This paper presents a model for optimizing the location of inventory for individual products in a multi-product two-echelon inventory system and the integration of those decisions into the location analysis for distribution centers. A realistic application of the analysis process is discussed.     

铁路客运站配套停车场泊位数量计算模型

铁路客运站配套停车场主要用于停靠接、送旅客的非营运车辆和出租车与其他社会车辆。在考虑接旅客车辆在停车场停留时间、旅客列车到达时刻、乘坐接旅客车辆人数等因素的基础上,构建接旅客车辆所需泊位数计算模型,采用系数法构建送旅客车辆和其他社会车辆所需泊位数计算模型,形成停车场泊位数量计算模型。以计算石家庄客运站停车场所需泊位数量为例,通过模型应用验证,分析模型的有效性。     

Multi-objective optimal planning for designing relief delivery systems

The fatal earthquake on September 21, 1999 caused significant damages to Taiwan, which made the national government focus on strengthening relief systems regarding natural disasters. Disaster prevention, protection, and reconstruction are the major areas of focus to reduce human suffering and damage from disasters. A key point is the ability to enhance the distribution of relief materials effectively. In this study, we construct a relief-distribution model using the multi-objective programming method for designing relief delivery systems in a real case. The model features three objectives: minimizing the total cost, minimizing the total travel time, and maximizing the minimal satisfaction during the planning period. The first two objectives pursue the efficiency goal, whereas the third pursue fairness – making best effort to ensure relief commodity delivery to all demand points. Results of an empirical study are presented and suggestions are given for future research.     

铁路军事交通运输保障能力的模糊聚类与粗糙决策

利用模糊集理论和粗糙集理论在处理不确定性和不精确性问题方面侧重点的差异性，构造一种组合决策模型，从铁路通达度、与公路贴近程度、通过受限情况以及“450”铁路国防交通储备物资库分布等4个角度对铁路军事交通运输保障能力进行了聚类与决策。     

Analysis of the effect of charging infrastructure design on electric taxi driving profiles: A case study approach on the example of Singapore

Replacing conventional vehicle taxis with electric vehicles would be an efficient measure to reduce greenhouse gas emissions. Due to the limited range and long charging times of current battery electric vehicles, it is of utmost importance to provide sufficient charging facilities. This article analyses the impact of the placement and charging power of charging stations on potential mileage and revenue of electric taxis on the example of Singapore. Therefore, we developed an agent-based electric taxi simulation model to investigate electric taxis’ driving profiles with respect to different vehicle types and charging infrastructure designs. This model is also capable of simulating conventional taxi driving profiles. The validation of these simulation results with real taxi data showed that the model is reproducing taxi driving profiles with high accuracy in great detail. We found out that electric taxis could reach the same mileage and revenue as conventional taxis if charging with a power of 160?kW is possible. Furthermore, we discovered that waiting times for available charging stations have a stronger effect on revenue than the length of detours to reach charging stations. Based on these findings, we concluded that it is more important to reduce waiting times by placing sufficient numbers of charging stations at each location before expanding the charging network by installing small numbers of charging stations at many locations.     

An integer programming approach to the bloodmobile routing problem

Every day, a blood center must determine a set of locations among a group of potential sites to route their vehicles for blood collection so as to avoid shortfalls. In this study, a vehicle routing problem is modeled using an integer programming approach to simultaneously identify number of bloodmobiles to operate and minimize the distance travelled. Additionally, the model is extended to incorporate uncertainty in blood potentials and variable durations in bloodmobile visits. Optimal routings are determined using CPLEX solver and branch-and-price algorithm. Results show that proposed algorithm solve the problem to optimality up to 30 locations within 3600 s.     

Conditions for electric vehicle taxi: A case study in the Greater Stockholm region

This study investigates the usability of electric vehicles (EVs) in a taxi company in Greater Stockholm, Sweden. By investigating cost and revenue data of both electric and conventional taxi vehicles, as well as by interviewing taxi drivers and carriers, an assessment has been made of the financial and operational implications of using EVs in a company’s taxi fleet. Both the drivers’ and the carriers’ perspectives have been examined. The main findings are that the investigated e-taxis have a similar or lower Total Cost of Ownership and slightly higher profitability than the investigated conventional taxis. For taxi drivers, using e-taxis implies more advanced planning and revenue service time being sacrificed for charging. However, certain customers’ preferences for EVs, as well as benefits such as corporate clients favoring e-taxis and a zero emission priority queuing system at Stockholm’s main international airport (partly) compensate for time devoted to charging. In order to facilitate increased use of e-taxis, more fast charging facilities should become available at strategic locations. Besides that, there are signs that carriers’ lack of information about the opportunities and consequences of shifting towards e-taxis hamper a wider deployment of e-taxis.     

Can public slow charging accelerate plug-in electric vehicle sales? A simulation of charging infrastructure usage and its impact on plug-in electric vehicle sales for Germany

Alternative fuel vehicles face the lack of refueling infrastructure as one obstacle to market diffusion and potential operators of refueling stations await significant market shares before constructing a dense refueling network. The resulting lock-in effect or chicken-egg-problem has scarcely been analyzed for plug-in electric vehicles (PEVs) up to now. The research question of this article is How much public charging infrastructure for PEVs is needed and is there mutual interaction in the diffusion of public charging infrastructure and electric vehicles?

Here, we present an agent-based market diffusion model for PEVs and their charging infrastructure that is based on a large number of individual driving profiles for private and commercial car holders in Germany. Our results demonstrate the possibility of a market diffusion in Germany without any slow public charging infrastructure until 2030. Although a charging point at home is obligatory for early adopters, the second-best option for an infrastructure set-up is at work where the majority of vehicles is parked for a long time during the day, the installation is not costly and users profit more than from public facilities. Public slow charging facilities do not increase PEV market shares and they need to be subsidized for a long time.     

Location optimisation method for fast-charging stations along national roads

Limited range of electric vehicles is still a huge barrier compared to conventional vehicles. A well-established charging station network, which is derived from users' charging demand, facilitates the spread of electric vehicles and lessens the range anxiety. Several methods have been developed for locating fast-charging stations along national roads in Europe according to the given objective function. In this paper, an arc-based location optimisation method realized by using a geographic information system and greedy algorithm is presented. An ‘oil stain’ deployment strategy is used to achieve even coverage with the minimum number of fast-charging stations along the roads. Several demographic, neighbourhood, and transport-related attributes, as well as the available services that influence the utilization of a fast-charging station, have been identified and their effects have been revealed in a systematic approach. The developed multi-criteria decision-making method has been applied to evaluate the rest areas along motorways and main roads and to propose deployment locations for fast-charging stations. The method was applied for Hungary as a case study and validated using real origin-destination (O-D) data. By the application of the locating method, the user can specify a network character by geographic parameters. The method can be especially beneficial if the O-D flows are unknown. Furthermore, the even distribution of the stations contributes to the high utilization of the fast-charging stations.