Efficient Operations at Intermodal Terminals Using a Multi-agent System

Trabalho apresentado em 12th Portuguese Conference on Automatic Control, 2016, Guimarães, Portugal, 2016info:eu-repo/semantics/publishedVersio

Criteria Impacting Synchronization of Transport Flows along International Transport Corridor

The main goal of this paper is to determine the main technical and technological criteria impacting the effectiveness of the synchronization of transport flows in the East-West Transport Corridor (EWTC) in the southern part of the Baltic Sea Region (BSR) corridor using a specific questionnaire. The results were processed using the Kendall rating correlation method, and the compatibility of the expert selection was analysed using a match factor. Following Kendall’s concordance coefficient and consistency ratio values, the expert opinions were reconciled. In the course of the research using the Average Rank Transformation into Weights (ARTIW) method, the normalized subjective weights of the main technical and technological impacting synchronization of transport flows were determined. The outcomes of the research presented in the paper have shown that the main technical criteria impacting synchronization are: railway infrastructure and road transport infrastructure at the terminals. The most important technological interaction criteria are accessibility of seaports and accessibility of railway distribution stations. In the following stages of research, the main criteria of the above two factors should be used to create models and facilitate synchronization with the purpose of building an interconnected transport system spanning all modes of transport. &nbsp;</p

Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review

Railway systems are time-varying and complex systems with nonlinear behaviors that require effective optimization techniques to achieve optimal performance. Evolutionary algorithms methods have emerged as a popular optimization technique in recent years due to their ability to handle complex, multi-objective issues of such systems. In this context, genetic algorithm (GA) as one of the powerful optimization techniques has been extensively used in the railway sector, and applied to various problems such as scheduling, routing, forecasting, design, maintenance, and allocation. This paper presents a review of the applications of GAs and their variants in the railway domain together with bibliometric analysis. The paper covers highly cited and recent studies that have employed GAs in the railway sector and discuss the challenges and opportunities of using GAs in railway optimization problems. Meanwhile, the most popular hybrid GAs as the combination of GA and other evolutionary algorithms methods such as particle swarm optimization (PSO), ant colony optimization (ACO), neural network (NN), fuzzy-logic control, etc with their dedicated application in the railway domain are discussed too. More than 250 publications are listed and classified to provide a comprehensive analysis and road map for experts and researchers in the field helping them to identify research gaps and opportunities

Digital Twins for Ports: Derived from Smart City and Supply Chain Twinning Experience

Ports are striving for innovative technological solutions to cope with the ever-increasing growth of transport, while at the same time improving their environmental footprint. An emerging technology that has the potential to substantially increase the efficiency of the multifaceted and interconnected port processes is the digital twin. Although digital twins have been successfully integrated in many industries, there is still a lack of cross-domain understanding of what constitutes a digital twin. Furthermore, the implementation of the digital twin in complex systems such as the port is still in its infancy. This paper attempts to fill this research gap by conducting an extensive cross-domain literature review of what constitutes a digital twin, keeping in mind the extent to which the respective findings can be applied to the port. It turns out that the digital twin of the port is most comparable to complex systems such as smart cities and supply chains, both in terms of its functional relevance as well as in terms of its requirements and characteristics. The conducted literature review, considering the different port processes and port characteristics, results in the identification of three core requirements of a digital port twin, which are described in detail. These include situational awareness, comprehensive data analytics capabilities for intelligent decision making, and the provision of an interface to promote multi-stakeholder governance and collaboration. Finally, specific operational scenarios are proposed on how the port's digital twin can contribute to energy savings by improving the use of port resources, facilities and operations.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

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

Planning and Scheduling Optimization

Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development

Models and Methods for Multi-Actor Systems

2010/2011The study of the models and methods to apply to multi-actor systems is a widely discussed research topic in the related scientific literature. The multi-actor systems are defined as systems that are characterized by the presence of several autonomous elements, of different decision makers and of complex rules that allow the communication, the coordination and the connection of the components of such systems. Commonly, the study of Multi-Actor System, MAS, recalls the well-known issues concerning the multi-agent systems. The research topic related to the multi-agent system firstly started to appear in scientific literature in 1980s, mainly in relation to the computer science and artificial intelligence. In this dissertation, in particular, the study of the multi-agent systems, and specifically of the multi-actor systems, is taken into account merely in relation to the distinctive features of complexity that characterize such systems and not to the issues concerning the agent-oriented software engineering. Therefore, the research results presented in this thesis are focused on the development and on the realization of innovative models and methodologies to face the management and the decision making mechanisms applied to complex multi-actor systems. This dissertation especially focuses on two different examples of multi-actor systems in two very diverse perspectives. The former deals with the research problem related to intermodal transportation networks, while the latter with the so called consensus problem in distributed networks of agents. Concerning the research problem related to the intermodal logistic systems, the research activity addresses the management of their more and more increasing complexity by the applications of the modern Information and Communication Technologies (ICT) tools that are key solutions to achieve the efficiency and to enhance logistics competitiveness. The related scientific literature still seems lacking in addressing with adequate attention the impact of these new techniques on the management of these complex systems and, moreover, there is an apparent lack of a systematic and general methodology to describe in detail the multiplicity of elements that can influence the dynamics and the corresponding information and decision making structure of intermodal transportation systems. The innovative results presented in this dissertation are focused on the development of an Integrated System, IS, devoted to manage intermodal transportation networks at the tactical as well as operational decision level to be used by decision makers both in off-line planning and real time management. To specify the Integrated System, a reference model is developed relying on a top-down metamodeling procedure. These innovative research results are a contribution to bridge the gap and to propose not only a systematic modeling approach devoted to describe a generic multi-actor logistic system, but also a management technique based on a closed loop strategy. The second example of application is focused on a topic that is widely discussed in scientific literature related to the study of the multi-actor collective behaviors in a distributed network. The interaction protocols that allow the agents to reach the convergence to a common value is called consensus or agreement problem. This research problem is particularly studied in the context of cooperative control of multi-agent systems because the agents are autonomous, independent and have to interact in a distributed network. The presented research results address the investigation of new and fast alignment protocols that enhance the performances of the standard iteration protocols for particular topologies of digraphs on the basis of a triangular splitting of the standard iteration matrix. The examined examples, the models and the methodologies applied to analyze them, are very different in the two cases and this testifies the large extent of research problems related to the multi-actor systems.L’analisi di modelli e metodi da sviluppare e da applicare nel contesto dei sistemi multi-attoriali costituisce un tema molto variegato e discusso nella letteratura scientifica internazionale. I sistemi multi-attoriali sono sistemi che si contraddistinguono per la presenza di molti elementi autonomi diversi tra loro, di molteplici decisori e di complesse regole che determinano la comunicazione, il coordinamento e la connessione all'interno di tali sistemi. Frequentemente, facendo riferimento a sistemi multi-attoriali, Multi-Actor Systems, si richiama il tema molto attuale dei sistemi multi agente, Multi-Agent Systems. Diffusisi a partire dal 1980, i sistemi multi agente sono spesso studiati in relazione alle metodologie di sviluppo dell'ingegneria del software. Nel presente lavoro di tesi, il tema dei sistemi multi-agente, ed in particolare di quelli multi-attoriali, non viene analizzato in questo contesto, ma in relazione alle tecniche decisionali da adottare per gestire sistemi caratterizzati da un alto livello di complessità. In tale ambito, i risultati presentati all'interno di questa dissertazione sono focalizzati sullo sviluppo e sulla realizzazione di nuovi metodi e di nuove metodologie, in grado di affrontare la gestione della complessità dei sistemi multi-attoriali. Vengono in particolare esaminate due diverse problematiche, in due contesti completamente diversi e con tecniche differenti, a testimoniare le vaste applicazioni che riguardano i sistemi multi-attoriali. I problemi analizzati sono incentrati, in primo luogo, su un'applicazione inerente la gestione di sistemi logistici intermodali ed, in secondo luogo, sullo studio delle regole o protocolli di interazione in una rete distribuita di agenti autonomi. Per quanto riguarda l'aspetto legato ai sistemi intermodali di trasporto, un tema molto discusso nella letteratura scientifica recente, l'analisi si focalizza sulla gestione della loro sempre crescente complessità, tramite l'utilizzo di sistemi dell'Information and Communication Technology, ICT. Questi strumenti richiedono metodi e modelli che sono innovativi rispetto a quanto è presente nella letteratura scientifica, all'interno della quale è stata riscontrata la mancanza di un approccio sistematico e sufficientemente ad alto livello per la realizzazione di una metodologia in grado di descrivere allo stesso tempo sia la molteplicità di elementi che influenzano le dinamiche e le informazioni, sia le strutture decisionali dei sistemi intermodali. L'innovazione dei risultati presentati in questa tesi si focalizza proprio sull'esigenza di proporre un sistema integrato, Integrated System (IS), basato su un metamodello delle reti intermodali di trasporto, che fornisca un valido supporto ai decisori sia a livello tattico che operativo. Il secondo aspetto affrontato in questa tesi riguarda un altro argomento di largo ed attuale interesse nella letteratura scientifica, che viene comunemente chiamato problema del consenso. Questo problema affronta lo studio di come diversi agenti autonomi collocati su una rete distribuita siano in grado di comunicare e di accordarsi su un valore comune, senza la presenza di un decisore centrale. A questo scopo ci sono degli algoritmi che specificano le regole o protocolli di interazione tra i diversi agenti. In tale contesto, i risultati proposti si focalizzano su alcune problematiche rappresentate dal protocollo classico del consenso e soprattutto sulla sua scarsa efficienza in particolari conformazioni delle reti di agenti. Il lavoro di tesi propone, quindi, un approccio di suddivisione, splitting, della matrice standard di iterazione, di tipo triangolare, che presenta notevoli vantaggi in termini di performance rispetto all'algoritmo classico. Lo studio di problemi multi-attoriali, pertanto, richiede lo sviluppo di innovative metodologie decisionali e di nuovi metodi di gestione delle comunicazioni, per rispondere al livello sempre crescente di complessità, offrendo in questo modo alcuni spunti molto interessanti per la ricerca.XXIV Ciclo198

Coastal vulnerability: Impact of port disruptions and the economic impacts of tropical cyclones

Coastal counties in the United States account for less than 10% of the nation’s land mass. Yet, approximately 40% of the country’s population, or over 127 million people, live in these areas. The population density of coastal counties is 461 people per square mile, much larger than the nation’s average population density of 87 people per square mile. Coasts also present the logistic benefit of allowing the transportation of goods between countries and continents through maritime ports. However, the increase in coastal population and economic activity means an increased exposure and vulnerability to potential natural hazards, such as hurricanes and tropical storms. These weather events are powerful, with the capacity to devastate coastal regions. Therefore, understanding these potentially catastrophic events is critical to assess vulnerability and support informed decision-making at local, state, and federal levels. This research provides valuable insights related to the characteristics of tropical cyclones and to their potential impacts to the coastal United States. First, an extensive review of the literature related to maritime supply chain resilience and the impacts of port disruptions to the maritime supply chain is performed. Ports are complex enterprises, comprised of a wide variety of stakeholders and subject to risks of many kinds, both man-made and natural hazards. This review allowed the identification of gaps of knowledge to be explored on the topic of maritime supply chain resilience. One of the gaps is the lack of a clearly quantifiable metric for the impacts of one of the most common sources of weather disruptions: hurricane and tropical storms. Albeit the immediate impacts are limited to areas prone to these events, tropical cyclones have been known to impact extensive areas and cause long lasting negative effects. Second, machine learning is used to rigorously explore and quantify the relationship of tropical cyclone characteristics and their destructive outcomes on the coast of the United States. Historical data on hurricanes and tropical storms is identified and curated to support supervised learning. A novel Storm Damage Ratio is introduced to address the inherent challenge of comparing damage to regions with distinct assets and population. Multiple mathematical models to predict economic impacts from tropical events are created using machine learning methods and the results are compared. Additionally, the storm features that most influence the accuracy of predictions are identified and ranked. The third research component consists in analyzing coastal vulnerability to tropical cyclones at the state-level by providing mechanisms to account for uncertainty in studying the destructive potential of storms, supporting the decision-making process to improve community resilience. The previously developed concept of Storm Damage Ratio is extended, creating the Local Storm Damage Ratio, which assess the destructive potential of storms with respect to intrinsic characteristics, regardless of the local economic characteristics. Multiple machine learning models are developed to predict the value of Local Storm Damage Ratio at a state-level. The most promising machine learning model is used to study the relationship between state and damage, as well as evaluate state preparedness. Finally, this work makes the innovative approach of building state-level empirical fragility curves to tropical storms. The novelty curves are built for three damage levels: minor, moderate, and major damage