Modeling the transit of containers through quay buffer storage zone in maritime terminals

The maritime container terminal allows the transfer of container flows from maritime vessels to the land transport network and vice versa. The transit capacity through the terminal is affected by the handling capacity of the equipment at the terminal, by the size of the storage areas and least by the technologies used in handling and storing the containers in the terminal. In this paper, the influence of these last two technologies on the duration of the process of unloading/loading of sea vessels within the terminal is analyzed. A discrete simulation model is used to evaluate the sizing method for short-term storage area located on the dock. The manner of allocating the flows of containers on it, as well as the working technology of the handling equipment, have an influence on the number of containers taken over, respectively loaded on the maritime vessels. The simulation model topology is developed following the existing physical structure of a container terminal from Constanta Port, in Romania. The obtained results can help the administration of the container terminal in optimizing the activity of handling, storing, and transferring the flows of containers from the maritime environment to the mainland and vice versa

Multi-objective Model on Connection Time Optimization in Sea-rail Intermodal Transport

Container sea-rail intermodal transport operation needs to consider some special demands both in volume and time connection. That means container sea-rail intermodal transport is a type of demand responsive transport between railroad trains and marine ships, vice versa. It needs to operate container trains according to the demands of ships in OD, volume, as well as the arrival and departure time. Basing on this responsive demand characteristic of sea-rail intermodal transport, the paper establishes a multi-objective optimal model for its connection time, aiming for maximizing the profits of carriers and minimizing the total transport costs of shippers, as well as minimizing the connection time between container trains and ships to optimizing the intermodal transport system. Modified genetic algorithm is adopted. The calculation results demonstrate that the model could be used to solve the connection problem of container sea-rail intermodal transport involved with volume and time connections

Sequence-Based Simulation-Optimization Framework With Application to Port Operations at Multimodal Container Terminals

It is evident in previous works that operations research and mathematical algorithms can provide optimal or near-optimal solutions, whereas simulation models can aid in predicting and studying the behavior of systems over time and monitor performance under stochastic and uncertain circumstances. Given the intensive computational effort that simulation optimization methods impose, especially for large and complex systems like container terminals, a favorable approach is to reduce the search space to decrease the amount of computation. A maritime port can consist of multiple terminals with specific functionalities and specialized equipment. A container terminal is one of several facilities in a port that involves numerous resources and entities. It is also where containers are stored and transported, making the container terminal a complex system. Problems such as berth allocation, quay and yard crane scheduling and assignment, storage yard layout configuration, container re-handling, customs and security, and risk analysis become particularly challenging. Discrete-event simulation (DES) models are typically developed for complex and stochastic systems such as container terminals to study their behavior under different scenarios and circumstances. Simulation-optimization methods have emerged as an approach to find optimal values for input variables that maximize certain output metric(s) of the simulation. Various traditional and nontraditional approaches of simulation-optimization continue to be used to aid in decision making. In this dissertation, a novel framework for simulation-optimization is developed, implemented, and validated to study the influence of using a sequence (ordering) of decision variables (resource levels) for simulation-based optimization in resource allocation problems. This approach aims to reduce the computational effort of optimizing large simulations by breaking the simulation-optimization problem into stages. Since container terminals are complex stochastic systems consisting of different areas with detailed and critical functions that may affect the output, a platform that accurately simulates such a system can be of significant analytical benefit. To implement and validate the developed framework, a large-scale complex container terminal discrete-event simulation model was developed and validated based on a real system and then used as a testing platform for various hypothesized algorithms studied in this work

Discrete-Event Control and Optimization of Container Terminal Operations

This thesis discusses the dynamical modeling of complex container terminal operations. In the current literature, the systems are usually modeled in static way using linear programming techniques. This setting does not completely capture the dynamic aspects in the operations, where information about external factors such as ships and trucks arrivals or departures and also the availability of terminal's equipment can always change. We propose dynamical modeling of container terminal operations using discrete-event systems (DES) modeling framework. The basic framework in this thesis is the DES modeling for berth and quay crane allocation problem (BCAP) where the systems are not only dynamic, but also asynchronous. We propose a novel berth and QC allocation method, namely the model predictive allocation (MPA) which is based on model predictive control principle and rolling horizon implementation. The DES models with asynchronous event transition is mathematically analyzed to show the efficacy of our method. We study an optimal input allocation problem for a class of discrete-event systems with dynamic input sequence (DESDIS). We show that in particular, the control input can be obtained by the minimization/maximization of the present input sequence only. We have shown that the proposed approach performed better than the existing method used in the studied terminal and state-of-the-art methods in the literature

Optimisation des systèmes de stockage de conteneurs dans les terminaux maritimes automatisés

AIn our study, we consider two optimization problems in automated container terminals at import; the first is the vehicle scheduling problem; and the second is the integrated problem of location assignment and vehicle scheduling. In the first part of our study, we propose different traffic layout adapted to the two studied problems and to every kind of automated container terminal. We also introduce relevant reviews of literature treating the optimization of container handling systems at maritime terminal, the optimization of general automated guided vehicle system and the multi-objective optimization in general, and in particular context of maritime container terminals. In the second part, we resolve the planning of QC-AV-ASC (Quay Cranes-Automated Vehicles - Automated Stacking Cranes). We present an effective model for every kind of traffic layout. Moreover, we propose an efficient bi-objective model which is important to determine the optimal storage time and the minimal number of required AVs. CPLEX resolutions are used to prove the efficiency of our modelling approach. In the third part of this thesis, we explore a problem which has not been sufficiently studied: the integrated problem of location assignment and vehicle scheduling (IPLAVS), in Maritime Automated Container Terminal (MACT) at import. This part represents a new and realistic approach of MACT optimization considering mono-objective and multi-objective aspect.Notre travail s’intéresse à un cas très particulier des terminaux à conteneurs, il s’agit des terminaux à conteneurs automatisés, qui en plus des véhicules autoguidés, sont équipés de grues de quai et de grues de stockage automatiques (grues de cour), ce qui pousse souvent les scientifiques à considérer les problèmes d’ordonnancement intégré dans les terminaux automatisés ou semi-automatisés. Nous traitons dans ce travail l’optimisation de plusieurs objectifs pour stocker les conteneurs d'une manière efficace et réaliste. Nous traitons le problème d’ordonnancement intégré considérant les trois équipements d’un terminal à conteneurs automatisé soient: les véhicules autoguidés, les grues de quai et les grues de baie (éventuellement). L’objectif principal de cette étude est la minimisation du coût opérationnel de stockage de conteneurs dans un terminal maritime automatis

Simulation model for optimization of a landside harbor logistic chain of container terminals.

The world wide transportation of all kind of goods with containers is a fast growing business. The challenge is to transport in the shortest time to the lowest cost. The vessels therefore become bigger and bigger. The biggest vessel with 16000 TEU is since December 2012 in service. But the next generation with 18000-22000 TEU is already being built. This raises questions in acceleration of loading and unloading process, the handling in the yards of the harbors and the transportation of the containers to Hinterland. The most common way is still to transport the container from the yard by truck, which causes a lot of traffic jams and pollution. With the growth of the volume and the limited space in most harbours the throughput in the yards must be dramatically increased. One possibility is to reduce multiple handling of the containers and to decentralize the transport to Hinterland. The idea of Dryports emerged several years ago. In this research a simulation model of all processes in the logistic chain is designed, with which all steps are linked together. A direct flow of the containers without any intermediate stocking in the yard. Todays average staytime of the containers in the yard of 3-4 days is completely deleted. The multiple handling is avoided. The variability of all input figures and constraints allows that the most real situations can be considered. Three different modalsplits are run in simulation. The results show, that it is possible to reduce the throughput time of the containers and the overall loading and unloading process of vessels in the harbor and to gain a high productivity. With the satellite model ( Dryport ) it is possible to reduce traffic in the yard and to avoid a lot of pollution. Overall shorter service times give an answer to the challenge of managing the future growth of the container business. The feasibility of the proposed model is confirmed

Hierarchical modeling and analysis of container terminal operations

After the breakdown of trade barriers among countries, the volume of international trade has grown significantly in the last decade. This explosive growth in international trade has increased the importance of marine transportation which constitutes the major part of the global logistics network. The utilization of containers and container ships in marine transportation has also increased after the eighties due to various advantages such as packaging, flexibility, and reliability. Parallel to the container throughput, the capacities of ships and sizes of fleets as well as the number of terminals have been increased considerably. Substantial pressure of competition on ship operators and terminal managers has forced them to consider the issues regarding operational efficiency more deeply. Thus, the operational efficiency at port container terminals has become the major concern of terminal managers to satisfy the rapid transshipment of goods. In this thesis, we focus on a set of decision problems regarding container terminal operations. Since these problems are interrelated hierarchically, we attempt to model and analyze them consecutively. First, we consider the storage space allocation problem over a rolling horizon as an aggregate planning model. Since the model has the minimum cost flow network structure there exist polynomial time solution procedures via linear programming models. Although ship turnaround time is the principal performance criteria for whole container terminal operations, the total distances traveled by containers in the terminal throughout the planning horizon is determined as the surrogate objective function for the allocation model. The output of the storage space allocation problem is used as the input for the next step of our methodology, namely the location matching model. With the location matching model, the routes of vehicles for each time period have been identified while minimizing the total distance traveled by the vehicles, which reveals the ship turnaround times. The routes that are found subject to the output of storage space allocation models are better than those of random allocation in terms of total distances traveled. Next, the vehicle scheduling problem is discussed for different levels of complexity. The solution procedures proposed for similar problems in the machine scheduling literature are provided. Finally, we discuss the problem of simultaneous vehicle dispatching with precedence constraints. We have modeled the problem as a nonlinear mixed integer programming model and proposed an iterative solution procedure to obtain reasonable solutions in considerable times. Moreover, we have presented the worst-case performance analysis for this heuristic

Simulation analysis for integrated container terminal activities

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