Models and new methods for the quayside operations in port container terminals.

Ph.DDOCTOR OF PHILOSOPH

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

Combinatorial Optimisation Problems in Logistics and Scheduling

This thesis presents a variety of problems and results in the fields of logistics and, in particular, of maritime and railways logistics. We first present a brief introduction to these problems, their characteristics, and the role they have in the quest for more efficient and greener global supply chains and transport systems; we also present the methodological tools employed for their solution. After this introduction, each chapter presents one specific problem, and corresponds to a self-contained research paper

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field

AIRO 2016. 46th Annual Conference of the Italian Operational Research Society. Emerging Advances in Logistics Systems Trieste, September 6-9, 2016 - Abstracts Book

The AIRO 2016 book of abstract collects the contributions from the conference participants. The AIRO 2016 Conference is a special occasion for the Italian Operations Research community, as AIRO annual conferences turn 46th edition in 2016. To reflect this special occasion, the Programme and Organizing Committee, chaired by Walter Ukovich, prepared a high quality Scientific Programme including the first initiative of AIRO Young, the new AIRO poster section that aims to promote the work of students, PhD students, and Postdocs with an interest in Operations Research. The Scientific Programme of the Conference offers a broad spectrum of contributions covering the variety of OR topics and research areas with an emphasis on “Emerging Advances in Logistics Systems”. The event aims at stimulating integration of existing methods and systems, fostering communication amongst different research groups, and laying the foundations for OR integrated research projects in the next decade. Distinct thematic sections follow the AIRO 2016 days starting by initial presentation of the objectives and features of the Conference. In addition three invited internationally known speakers will present Plenary Lectures, by Gianni Di Pillo, Frédéric Semet e Stefan Nickel, gathering AIRO 2016 participants together to offer key presentations on the latest advances and developments in OR’s research

The impact of automation on the efficiency and cost effectiveness of the quayside and container yard cranes and the selection decision for the yard operating systems

This research evaluates the impact of automated and semi-automated devices on the process of loading, discharging, stacking and un-stacking of containers using Quayside Cranes (QSCs), Straddle Carriers (SCs), Rubber Tyred Gantry cranes (RTGs) and Rail Mounted Gantry cranes (RMGs) in container terminals. The emphasis of study is on the assessment of performance and cost effectiveness of the existing automated quayside and yard cranes. The study in this thesis examines the economic implications of reducing QSCs' cycle-times brought about by automatic features installed on the post-Panamax cranes. It demonstrates that a considerable increase in the productivity of QSCs is related directly or indirectly to an expected reduction of crane cycle-times. The concept offered by the proposed improvements distinguishes between the traditional system of loading and discharging of containers and the automated methods. It implies that automation devices installed on conventional QSCs significantly reduce the total turnaroundtime and hence the cost of containerships' waiting-times. It argues, however, that there should be a balance between the cost of containerships' waiting-times and the cost of automated berths' unproductive-times (idle-times). This study uses the elements of queuing theories and proposes a novel break-even method for calculating such a balance. The number of container Ground Slots (GSs) and the annual throughput of container terminals expressed in Twenty-foot Equivalent Units (TEUs) have been used as the efficiency and performance measure for many years. The study in this thesis introduces appropriate container yard design layouts and provides a generic model for calculating the annual throughput for container terminals using semiautomated SC and RTG and automated and semi-automated RMG operating systems. The throughput model proposed in this study incorporates the dynamic nature, size, type and capacity of the automated container yard operating systems and the average dwell-times, transhipment ratio, accessibility and stacking height of the containers as the salient factors in determining a container terminal throughput. Further, this thesis analyses the concept of cost functions for container yard operating systems proposed. It develops a generic cost-based model that provides the basis for a pair-wise comparison, analysis and evaluation of the economic efficiency and effectiveness of automated and semi-automated container yard stacking cranes and helps to make rational decisions. This study proposes a Multiple Attribute Decision-Making (MADM) method for evaluating and selecting the best container yard operating system amongst alternatives by examining the most important operating criteria involved. The MADM method proposed enables a decision-maker to study complex problems and allows consideration of qualitative and qualitative attributes that are heterogeneous in nature. An Analytical Hierarchy Process (AHP) technique has been employed as a weighting method to solve the MADM problem. The AHP allows for the decomposition of decision problem into a hierarchical order and enables a pair-wise comparison of the attributes and alternatives. The results of the AHP analysis provide the basis for a pair-wise comparison, judgement and selection of the best automated or semi-automated container yard operating system

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management