A rolling horizon algorithm for auto-carrier transportation

This paper introduces a rolling horizon algorithm to plan the delivery of vehicles to automotive dealers by a heterogeneous fleet of auto-carriers. The problem consists in scheduling the deliveries over a multiple-day planning horizon during which requests for transportation arrive dynamically. In addition, the routing of the auto-carriers must take into account constraints related to the loading of the vehicles on the carriers. The objective is to minimize the sum of traveled distances, fixed costs for auto-carrier operation, service costs, and penalties for late deliveries. The problem is solved by a heuristic that first selects the vehicles to be delivered in the next few days and then optimizes the deliveries by an iterated local search procedure. A branch-and-bound search is used to check the feasibility of the loading. To handle the dynamic nature of the problem, the complete algorithm is applied repeatedly in a rolling horizon framework. Computational results on data from a major European logistics service provider show that the heuristic is fast and yields significant improvements compared to the sequential solution of independent daily problems.     

The desulphurisation of shipping: Past,present and the future under a global cap

As from January 2020, the International Maritime Organization (IMO) is implementing a global 0.5% limit on the sulphur content of fuel, commonly known as the global sulphur cap. This limit is the latest policy in the efforts to reduce sulphur emissions from shipping, following the designation of emission control areas (ECAs) and other regional regulations. In this paper, a literature review is conducted of academic studies that have dealt with issues relating to the reduction of maritime sulphur emissions. Various recurring research themes are identified, spanning the areas of operations research, maritime economics and transport policy. The effects and implications of available compliance options are then analyzed from the perspectives of ship operators, shippers and consumers. Using lessons learned from the enforcement of ECA regulations, this is followed by an appraisal of various potential issues related to the enforcement of these new global regulations. It is found that a homogeneous enforcement regime is required to ensure a level playing field amongst ship operators and that the global sulphur cap may lead to serious market distortion, due to the potential short term rise of fuel prices. The paper concludes with a set of recommendations for future research on sulphur emissions from shipping in the aftermath of the global cap and, looking forward, to its relationship to the IMO strategy on the reduction of greenhouse gas (GHG) shipping emissions.     

Key beliefs and attitudes for sea-level rise policy

This article reviews key measures of public opinion on sea-level rise (SLR): beliefs, attitudes, issue prioritization, and policy support. To do so, we first assess the influence of SLR beliefs and attitudes on issue prioritization and policy support using state-level data. Then, we compare the state findings to other surveys conducted in a hot spot of rising coastal waters, the U.S. Mid-Atlantic, to better understand the landscape of public opinion. Our findings indicate that, as in studies of climate change public opinion, belief certainty that SLR is happening and attitudes about its consequences significantly influence issue prioritization and policy support. Compared to climate change, SLR demonstrates less salience, but is similarly a low public priority. Nevertheless, the public supports governmental policies that address the issue, preferring strategies that discourage new construction in high risk areas and employ “soft” protection through natural barriers. Among the least popular approaches are those that implement hard barriers to defend against encroaching seas. Communication programs and public consultation by governments can benefit from the use of survey data to support evidence-based decision-making.     

Agent-based simulation framework for mixed traffic of cars,pedestrians and trams

In this paper, we report on the construction of a new framework for simulating mixed traffic consisting of cars, trams, and pedestrians that can be used to support discussions about road management, signal control, and public transit. Specifically, a layered road structure that was designed for car traffic simulations was extended to interact with an existing one-dimensional (1D) car-following model and a two-dimensional (2D) discrete choice model for pedestrians. The car model, pedestrian model, and interaction rules implemented in the proposed framework were verified through simulations involving simple road environments. The resulting simulated values were in near agreement with the empirical data. We then used the proposed framework to assess the impact of a tramway extension plan for a real city. The simulation results showed that the impact of the proposed tramway on existing car traffic would not be serious, and by extension, implied that the proposed framework could help stakeholders decide on expansion scenarios that are satisfactory to both tram users and private car owners.     

The load-dependent vehicle routing problem and its pick-up and delivery extension

The present paper examines a Vehicle Routing Problem (VRP) of major practical importance which is referred to as the Load-Dependent VRP (LDVRP). LDVRP is applicable for transportation activities where the weight of the transported cargo accounts for a significant part of the vehicle gross weight. Contrary to the basic VRP which calls for the minimization of the distance travelled, the LDVRP objective is aimed at minimizing the total product of the distance travelled and the gross weight carried along this distance. Thus, it is capable of producing sensible routing plans which take into account the variation of the cargo weight along the vehicle trips. The LDVRP objective is closely related to the total energy requirements of the vehicle fleet, making it a credible alternative when the environmental aspects of transportation activities are examined and optimized. A novel LDVRP extension which considers simultaneous pick-up and delivery service is introduced, formulated and solved for the first time. To deal with large-scale instances of the examined problems, we propose a local-search algorithm. Towards an efficient implementation, the local-search algorithm employs a computational scheme which calculates the complex weighted-distance objective changes in constant time. Solution results are presented for both problems on a variety of well-known test cases demonstrating the effectiveness of the proposed solution approach. The structure of the obtained LDVRP and VRP solutions is compared in pursuit of interesting conclusions on the relative suitability of the two routing models, when the decision maker must deal with the weighted distance objective. In addition, results of a branch-and-cut procedure for small-scale instances of the LDVRP with simultaneous pick-ups and deliveries are reported. Finally, extensive computational experiments have been performed to explore the managerial implications of three key problem characteristics, namely the deviation of customer demands, the cargo to tare weight ratio, as well as the size of the available vehicle fleet.     

Are technology myths stalling aviation climate policy?

Emissions from aviation will continue to increase in the future, in contradiction of global climate policy objectives. Yet, airlines and airline organisations suggest that aviation will become climatically sustainable. This paper investigates this paradox by reviewing fuel-efficiency gains since the 1960s in comparison to aviation growth, and by linking these results to technology discourses, based on a two-tiered approach tracing technology-focused discourses over 20 years (1994–2013). Findings indicate that a wide range of solutions to growing emissions from aviation have been presented by industry, hyped in global media, and subsequently vanished to be replaced by new technology discourses. Redundant discourses often linger in the public domain, where they continue to be associated with industry aspirations of ‘sustainable aviation’ and ‘zero-emission flight’. The paper highlights and discusses a number of technology discourses that constitute ‘technology myths’, and the role these ‘myths’ may be playing in the enduring but flawed promise of sustainable aviation. We conclude that technology myths require policy-makers to interpret and take into account technical uncertainty, which may result in inaction that continues to delay much needed progress in climate policy for aviation.     

基于前轮转角约束自适应模型预测控制的路径跟踪研究

针对在车辆行驶中较小的前轮转角无法充分利用路面附着能力,较大的前轮转角使得车辆的行驶稳定性差的问题,文章提出了一种前轮转角约束自适应模型预测方法。首先建立车辆的动力学模型,然后通过计算得到轮胎纵向力,最终得到车辆的前轮转角。将车辆的状态量与前轮转角自适应约束条件输入给模型预测控制器,输出车辆的前轮转角,实现对参考路径的跟踪。在Carsim和MATLAB平台上联合仿真,仿真结果表明前轮转角约束自适应模型预测控制的车辆相比固定转角约束的车辆具有较好的跟踪能力和稳定性。     

A real-time adaptive signal control in a connected vehicle environment

The state of the practice traffic signal control strategies mainly rely on infrastructure based vehicle detector data as the input for the control logic. The infrastructure based detectors are generally point detectors which cannot directly provide measurement of vehicle location and speed. With the advances in wireless communication technology, vehicles are able to communicate with each other and with the infrastructure in the emerging connected vehicle system. Data collected from connected vehicles provides a much more complete picture of the traffic states near an intersection and can be utilized for signal control. This paper presents a real-time adaptive signal phase allocation algorithm using connected vehicle data. The proposed algorithm optimizes the phase sequence and duration by solving a two-level optimization problem. Two objective functions are considered: minimization of total vehicle delay and minimization of queue length. Due to the low penetration rate of the connected vehicles, an algorithm that estimates the states of unequipped vehicle based on connected vehicle data is developed to construct a complete arrival table for the phase allocation algorithm. A real-world intersection is modeled in VISSIM to validate the algorithms. Results with a variety of connected vehicle market penetration rates and demand levels are compared to well-tuned fully actuated control. In general, the proposed control algorithm outperforms actuated control by reducing total delay by as much as 16.33% in a high penetration rate case and similar delay in a low penetration rate case. Different objective functions result in different behaviors of signal timing. The minimization of total vehicle delay usually generates lower total vehicle delay, while minimization of queue length serves all phases in a more balanced way.     

Robust weekly aircraft maintenance routing problem and the extension to the tail assignment problem

In this paper, we study two closely related airline planning problems: the robust weekly aircraft maintenance routing problem (RWAMRP) and the tail assignment problem (TAP). In real life operations, the RWAMRP solution is used in tactical planning whereas the TAP solution is implemented in operational planning. The main objective of these two problems is to minimize the total expected propagated delay (EPD) of the aircraft routes. To formulate the RWAMRP, we propose a novel weekly line-of-flights (LOF) network model that can handle complex and nonlinear cost functions of EPD. Because the number of LOFs grows exponentially with the number of flights to be scheduled, we propose a two-stage column generation approach to efficiently solve large-scale real-life RWAMRPs. Because the EPD of an LOF is highly nonlinear and can be very time-consuming to accurately compute, we propose three lower bounds on the EPD to solve the pricing subproblem of the column generation. Our approach is tested on eight real-life test instances. The computational results show that the proposed approach provides very tight LP relaxation (within 0.6% of optimal solutions) and solves the test case with more than 6000 flights per week in less than three hours. We also investigate the solutions obtained by our approach over 500 simulated realizations. The simulation results demonstrate that, in all eight test instances, our solutions result in less EPDs than those obtained from traditional methods. We then extend our model and solution approach to solve realistically simulated TAP instances.     

Generalized Maximum Benefit Multiple Chinese Postman Problem

This research is focused on a generalization on the Max Benefit Chinese Postman Problem and the multiple vehicle variant of the Chinese Postman Problem. We call this generalization, the Generalized Maximum Benefit k-Chinese Postman Problem (GB k-CPP). We present a novel Mixed Integer Programming (MIP) formulation for the GB k-CPP. Four different cases of the model are discussed. The first case, performs arc-routing with profits and assumes that the origin and destination for each vehicle is the same for each cycle and is given by the user. The next case relaxes the assumption that the origin and destination for each vehicle should be the same and allows the users to select possible origins/destinations for vehicles. Case three gets the origin for each vehicle as input and produces a solution based on finding the best destination for each vehicle. The last case, that is very general, allows the optimization model to select possibly different locations for vehicle origin and destination, during each cycle. The different cases are applied to a security patrolling case conducted on the network of University of Maryland at College Park campus and the results are compared.