Sea Container Terminals

Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations

Human Ergonomic Simulation to Support the Design of an Exoskeleton for Lashing/De-Lashing Operations of Containers Cargo

Lashing and de-lashing operations of containers cargo on board containerships are considered as quite strenuous activities in which operators are required to work continuously over a 6 or 8 hours shift with very limited break. This is mostly because containerships need to leave the port as soon as possible and containers loading and unloading operations must be executed with very high productivity (stay moored in a port is a totally unproductive time for a ship and a loss-making business for a shipping company). Operators performing lashing and de-lashing operations are subjected to intense ergonomic stress and uncomfortable working postures. To this end, the authors of this article are participating to a research project for the design of an exoskeleton that will help operators to reduce ergonomics and working posture problems while increasing, at the same time, the productivity. This paper presents the results of a human ergonomic simulation devoted t

Vehicle Dispatching Problem at the Container Terminal with Tandem Lift Quay Cranes

The most important issue at a container terminal is to minimize the ship’s turnaround time which is determined by the productivities of quay cranes (QCs). The tandem lift quay cranes have 33% higher productivities than single lift QCs. However, the tandem lift operations bring new challenges to the vehicle dispatching at terminals and this has become a big issue in the application of tandem lift QCs. The vehicle dispatching at terminals is to enhance the QCs’ productivities by coordinating the QCs’ operation schedules and the vehicles’ delivery schedules. The static version of the problem can be formulated as an MILP model and it is a combinational optimization problem. When the type of QC is tandem lift, the problem becomes more complicated because it requires two vehicles side by side under the QC. Thus, the alignments of vehicles have to be considered by coordinating the delivery schedules between vehicles. On the other hand, because the containers are operated alone by the yard cranes, the vehicles could not be grouped and dispatched in pairs all the time. This dissertation investigates the static and dynamic version of the problem and proposes heuristic methods to solve them. For the static version, Local Sequence Cut (LSC) Algorithm is proposed to tighten the search space by eliminating those feasible but undesirable delivery sequences. The time windows within which the containers should be delivered are estimated through solving sub-problems iteratively. Numerical experiments show the capability of the LSC algorithm to find competitive solutions in substantially reduced CPU time. To deal with the dynamic and stochastic working environment at the terminal, the dissertation proposes an on-line dispatching rule to make real-time dispatching decisions without any information of future events. Compared with the longest idle vehicle rule, the proposed priority rule shortens the makespan by 18% and increases the QCs’ average productivities by 15%. The sensitivity analysis stated that the superiority of the priority rule is more evident when the availability of vehicles is not sufficient compared with the frequency of releasing transportation requests

Control of free-ranging automated guided vehicles in container terminals

Container terminal automation has come to the fore during the last 20 years to improve their efficiency. Whereas a high level of automation has already been achieved in vertical handling operations (stacking cranes), horizontal container transport still has disincentives to the adoption of automated guided vehicles (AGVs) due to a high degree of operational complexity of vehicles. This feature has led to the employment of simple AGV control techniques while hindering the vehicles to utilise their maximum operational capability. In AGV dispatching, vehicles cannot amend ongoing delivery assignments although they have yet to receive the corresponding containers. Therefore, better AGV allocation plans would be discarded that can only be achieved by task reassignment. Also, because of the adoption of predetermined guide paths, AGVs are forced to deploy a highly limited range of their movement abilities while increasing required travel distances for handling container delivery jobs. To handle the two main issues, an AGV dispatching model and a fleet trajectory planning algorithm are proposed. The dispatcher achieves job assignment flexibility by allowing AGVs towards to container origins to abandon their current duty and receive new tasks. The trajectory planner advances Dubins curves to suggest diverse optional paths per origin-destination pair. It also amends vehicular acceleration rates for resolving conflicts between AGVs. In both of the models, the framework of simulated annealing was applied to resolve inherent time complexity. To test and evaluate the sophisticated AGV control models for vehicle dispatching and fleet trajectory planning, a bespoke simulation model is also proposed. A series of simulation tests were performed based on a real container terminal with several performance indicators, and it is identified that the presented dispatcher outperforms conventional vehicle dispatching heuristics in AGV arrival delay time and setup travel time, and the fleet trajectory planner can suggest shorter paths than the corresponding Manhattan distances, especially with fewer AGVs.Open Acces

Modeling and Design of Container Terminal Operations

Design of container terminal operations is complex because multiple factors affect the operational perfor- mance. These factors include: topological constraints, a large number of design parameters and settings, and stochastic interactions that interplay among the quayside, vehicle transport, and stackside processes. In this research, we propose new integrated queuing network models for rapid design evaluation of container terminals with Automated Lift Vehicles (ALVs) and Automated Guided Vehicles (AGVs). These models offer the flexibility to analyze alternate design variations and develop insights. For instance, the effect of alternate vehicle dwell point policy is analyzed using state-dependent queues, whereas the efficient terminal layout is determined using variation in the service time expressions at the stations. Further, using embedded Markov chain analysis, we develop an approximate procedure for analyzing bulk container arrivals. These models form the building block for design and analysis of large-scale terminal operations. We test the model efficacy using detailed in-house simulation experiments and real-terminal validation by partnering with an external party

Simulation analysis for integrated container terminal activities

Analisi simualtiva delle attività  logistiche di un container terminal con utilizzo del software Arenaope