A ‘Less-flexibility-first’ Heuristic for the Placement of Inland Vessels in a Lock

Abstract

Inland vessels move goods along waterways (canals and rivers) and they visit ports. Because of their tidal nature, vessels make use of locks to enter ports or waterways. From a port management point of view, fast access to and from the port and high utilization of locks are important objectives. Where the former relates to low inbound and outbound waiting times, the latter relates to the placement of as many vessels as possible in the lock before its operation. This article includes a case study that relates to the operation of the Van Cauwelaert lock in the port of Antwerp, Belgium. Lock operation policy is as follows: vessels wait in front of the lock for a port administrator to assign places in the lock based on knowledge of the vessels’ dimensions. As such, there is no FIFO-discipline, but a ‘group-FIFO’-discipline, i.e. if n vessels are allowed into the lock, they are the first n vessels in the arrival queue. A heuristic algorithm is formulated for the placement of vessels in the lock. This algorithm supports the decision where to place the vessel in the lock, aiming to place as many vessels as possible from the arrival queue. At the same time, it supports the decision to start a locking operation or not, based on information about vessels that are announced but which have not yet arrived at the lock's entrance. The heuristic is called a ‘less-flexibility-first’-heuristic as it looks for pseudo-placements, showing which flexibility is left for the remaining vessels after placing a vessel. This article describes the implementation of the heuristic and provides numerical examples. A comparison is made between the heuristic results and daily practice, based on real-life vessel movements through the Van Cauwelaert lock in 2002.     

Evaluating the operational performance of airside and landside at Chinese airports with novel inputs

ABSTRACT

This paper evaluates the operational performance of airside and landside at Chinese airports with two novel inputs. Furthermore, the airport landside operation is decomposed into passenger-terminal operations and cargo-warehouse operations. One novel input is the capability of the runway system which is introduced into airside performance evaluation. The other novel input is cargo warehousing which is introduced into landside performance evaluation. To address multiple optimal solutions when estimating Returns to Scale in Data Envelopment Analysis, we adopted the Zhu and Shen method. This empirical study shows that neither the number of runways nor total runway length is a genuine index of runway system capability in the evaluation of airside performance. Only four airports achieved full efficiency in all eight measures while eight airports did not achieve any full efficiency. In addition, one airport did not perform well in the benchmark analysis.     

移动互联网技术在高速公路的应用展望

随着移动互联网技术的发展和用户数量的快速增长,其应用领域也在不断深化拓展,催生了很多新的应用模式.对于高速公路这一传统领域,移动互联网技术一方面可以作为高速企业和行业主管单位业务推广的手段,另一方面也重构了其业务模式,在移动信息发布、交通流量分析、移动数据传输以及车路联网等方面形成了全新的应用方式,深刻地影响和改变了高速公路的管理模式.     

Application of El Farol model for managing marine terminal gate congestion

Truck queuing at marine terminal gates has long been recognized as a source of emissions problem due to the large number of trucks idling. For this reason, there is a great deal of interest among the different stakeholders to lessen the severity of the problem. An approach being experimented by some terminals to reduce truck queuing at the terminal is to provide live views of their gates via webcams. An assumption made by the terminals in this method is that truck dispatchers and drivers will make rational decisions regarding their departure times such that there will be less fluctuations in truck arrivals at the terminal based on the live information. However, it is clear that if dispatchers send trucks to the terminal whenever the truck queues are short and not send trucks when the truck queues are long, it could lead to a perpetual whip lash effect. This study explores the predictive strategies that need to be made by the various dispatchers to achieve the desired effects (i.e. steady arrival of trucks and hence less queuing at the seaport terminal gates). This problem is studied with the use of an agent-based simulation model and the solution to the well known El Farol Bar problem. Results demonstrate that truck depots can manage (without any collaboration with one another) to minimize congestion at seaport terminal gates by using the provided real-time gate congestion information and some simple logics for estimating the expected truck wait time.     

港口物流企业联盟及其运营调度优化

港口物流企业联盟是近年来发展起来的一种新型的港口物流企业组织形式,对社会和企业有利。介绍了联盟实现方式、组织结构设计原则、运营调度及其优化研究现状,给出了港口物流企业联盟运营调度优化模型建立实例,根据实例的运算结果,证明了该港口物流企业联盟的运营调度优化模式是可行的,在港口物流企业联盟的调度过程中具有一定的实用性。     

Reducing bunching with bus-to-bus cooperation

Schedule-based or headway-based control schemes to reduce bus bunching are not resilient because they cannot prevent buses from losing ground to the buses they follow when disruptions increase the gaps separating them beyond a critical value. (Following buses are then overwhelmed with passengers and cannot process their work quick enough to catch up.) This critical gap problem can be avoided, however, if buses at the leading end of such gaps are given information to cooperate with the ones behind by slowing down.This paper builds on this idea. It proposes an adaptive control scheme that adjusts a bus cruising speed in real-time based on both, its front and rear spacings much as if successive bus pairs were connected by springs. The scheme is shown to yield regular headways with faster bus travel than existing control methods. Its simple and decentralized logic automatically compensates for traffic disruptions and inaccurate bus driver actions. Its hardware and data requirements are minimal.     

宁波原舟山港穿山港区集装箱作业区与穿山疏港高速公路的有机衔接

宁波-舟山港穿山港区集装箱作业区将建成11个7万～10万吨级集装箱泊位,公路集疏运量将达到700万TEU,实现该作业区与穿山疏港高速公路的有机衔接将很好地解决公路集疏运问题,提升港口服务水平。通过分析穿山港区集疏运现状,预测公路集疏运量和对外交通量;并根据港区总平面布置、周边用地情况及《公路路线设计规范》的有关规定,综合确定穿山港区集装箱作业区与穿山疏港高速公路的衔接方案。     

Operating cost sensitivity to required time of arrival commands to ensure separation in optimal aircraft 4D trajectories

Trajectory optimisation has shown good potential to reduce environmental impact in aviation. However, a recurring problem is the loss in airspace capacity that fuel optimal procedures pose, usually overcome with speed, altitude or heading advisories that lead to more costly trajectories. This paper aims at the quantification in terms of fuel and time consumption of implementing suboptimal trajectories in a 4D trajectory context that use required times of arrival at specific navigation fixes. A case study is presented by simulating conflicting Airbus A320 departures from two major airports in Catalonia. It is shown how requiring an aircraft to arrive at a waypoint early or late leads to increased fuel burn. In addition, the efficiency of such methods to resolve air traffic conflicts is studied in terms of both fuel burn and resulting aircraft separations. Finally, various scenarios are studied reflecting various airline preferences with regards to cost and fuel burn, as well as different route and conflict geometries for a broader scope of study.     

Modeling taxi drivers’ decisions for improving airport ground access: John F. Kennedy airport case

Taxi service is an important component of airport ground access, which affects the economic competitiveness of an airport and its potential positive impact on the surrounding region. Airports across the globe experience both taxi shortages and excesses due to various factors such as the airport’s proximity to the city center, timing and frequency of flights, and the fare structure. Since taxi drivers are independent entities whose decisions affect the taxi supply at airports, it is important to understand taxi drivers’ decision mechanisms in order to suggest policies and to maintain taxi demand and supply equilibrium at the airports. In this paper, New York City (NYC) taxi drivers’ decisions about airport pick-ups or cruising for customers at the end of each trip is modeled using logistic regression based on a large taxi GPS dataset. The presented approach helps to quantify the potential impacts of parameters and to rank their influence for policy recommendations. The results reveal that spatial variables (mainly related to proximity) have the highest impact on taxi drivers’ airport pickup decisions, followed by temporal, environmental and driver-shift related variables. Along with supplementary information from unstructured taxi driver interviews, the model results are used to suggest policies for the improvement of John F. Kennedy (JFK) airport’s ground access and passenger satisfaction, i.e. the implementation of taxi driver frequent airport server punch cards and a time-specific ride share program.     

Airline-driven ground delay programs: A benefits assessment

Three decades of research studies in ground delay program (GDP) decision-making, and air traffic flow management in general, have produced several analytical models and decision support tools to design GDPs with minimum delay costs. Most of these models are centralized, i.e., the central authority almost completely decides the GDP design by optimizing certain centralized objectives. In this paper, we assess the benefits of an airline-driven decentralized approach for designing GDPs. The motivation for an airline-driven approach is the ability to incorporate the inherent differences between airlines when prioritizing, and responding to, different GDP designs. Such differences arise from the airlines’ diverse business objectives and operational characteristics. We develop an integrated platform for simulating flight operations during GDPs, an airline recovery module for mimicking the recovery actions of each individual airline under a GDP, and an algorithm for fast solution of the recovery problems to optimality. While some of the individual analytical components of our framework, model and algorithm share certain similarities with those used by previous researchers, to the best of our knowledge, this paper presents the first comprehensive platform for simulating and optimizing airline operations under a GDP and is the most important technological contribution of this paper. Using this framework, we conduct detailed computational experiments based on actual schedule data at three of the busiest airports in the United States. We choose the recently developed Majority Judgment voting and grading method as our airline-driven decentralized approach for GDP design because of the superior theoretical and practical benefits afforded by this approach as shown by multiple recent studies. The results of our evaluation suggest that adopting this airline-driven approach in designing the GDPs consistently and significantly reduces airport-wide delay costs compared to the state-of-the-research centralized approaches. Moreover, the cost reduction benefits of the resultant airline-driven GDP designs are equitably distributed across different airlines.