9 research outputs found

    Berth Scheduling at Seaports: Meta-Heuristics and Simulation

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    This research aims to develop realistic solutions to enhance the efficiency of port operations. By conducting a comprehensive literature review on logistic problems at seaports, some important gaps have been identified for the first time. The following contributions are made in order to close some of the existing gaps. Firstly, this thesis identifies important realistic features which have not been well-studied in current academic research of berth planning. This thesis then aims to solve a discrete dynamic Berth allocation problem (BAP) while taking tidal constraints into account. As an important feature when dealing with realistic scheduling, changing tides have not been well-considered in BAPs. To the best of our knowledge, there is no existing work using meta-heuristics to tackle the BAP with multiple tides that can provide feasible solutions for all the test cases. We propose one single-point meta-heuristic and one population-based meta-heuristic. With our algorithms, we meet the following goals: (i) to minimise the cost of all vessels while staying in the port, and (ii) to schedule available berths for the arriving vessels taking into account a multi-tidal planning horizon. Comprehensive experiments are conducted in order to analyse the strengths and weaknesses of the algorithms and compare with both exact and approximate methods. Furthermore, lacking tools for examining existing algorithms for different optimisation problems and simulating real-world scenarios is identified as another gap in this study. This thesis develops a discrete-event simulation framework. The framework is able to generate test cases for different problems and provide visualisations. With this framework, contributions include assessing the performance of different algorithms for optimisation problems and benchmarking optimisation problems

    Essays on Port, Container, and Bulk Chemical Logistics Optimization

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    The essays in this thesis are concerned with two main themes in port logistics. The first theme is the coordination of transport arrivals with the distribution processes and the use of storage facilities. We study this for both containerized and bulk chemical transport. The second theme is the uncertainty associated with the arrival time of ships with bulk chemicals and the impact on port logistics. Each essay describes a case study where quantitative methods, especially simulation, are used. The operation of container terminals and in particular the way in which containers are stacked in a yard is influenced by information about the departure of a container. We find that even inaccurate information is valuable and helps to reduce unproductive moves. Next, we present the ``floating stocks'' distribution concept which uses intermodal transport to deploy inventories in a supply chain in advance of retailer demand. We demonstrate that a main drawback of intermodal transport, a longer transit time, can be mitigated using this concept. This concept also influences the choice of a port: we provide a quantitative interpretation of routing flexibility in port selection

    Metaheuristic approach for solving one class of optimization problems in transport

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    Problem dodele vezova obuhvata nekoliko važnih odluka koje je potrebno doneti da bi se dosegla maksimalna efikasnost luke. U luci, menadžeri terminala treba da dodele slobodne vezove brodovima koji su najavili dolazak...Berth Allocation Problem incorporates some of the most important decisions that have to be made in order to achieve maximum eciency in a port. Terminal manager of a port has to assign incoming vessels to the available berths, where they will be loaded/unloaded in such a way that some objective function is optimized. It is well known that even the simpler variants of Berth Allocation Problem are NP-hard, and thus, metaheuristic approaches are more convenient than exact methods, because they provide high quality solutions in reasonable computational time. This study considers two variants of the Berth Allocation Problem: Minimum Cost Hybrid Berth AllocationProblem (MCHBAP) and Dynamic Minimum Cost Hybrid Berth AllocationProblem (DMCHBAP), both with xed handling times of vessels. Objective function to be minimized consists of the following components: costs of positioning, speeding up or waiting of vessels, and tardiness of completion for all vessels. Having in mind that the speed of nding high-quality solutions is of crucial importance for designing an ecient and reliable decision support system in container terminal, metaheuristic methods represent the natural choice when dealing with MCHBAP and DMCHBAP. This study examines the following metaheuristic approaches for both types of a given problem: two variants of the Bee Colony Optimization (BCO), two variants of the Evolutionary Algorithm (EA), and four variants of Variable Neighborhood Search (VNS). All metaheuristics are evaluated and compared against each other and against exact methods integrated in commercial CPLEX solver on real-life instances from the literature and randomly generated instances of higher dimensions. The analysis of the obtained results shows that on real-life instances all metaheuristics were able to nd optimal solutions in short execution times. Randomly generated instances were out of reach for exact solver due to time or memory limits, while metaheuristics easily provided high-quality solutions in short CPU time in each run. The conducted computational analysis indicates that metaheuristics represent a promising approach for MCHBAP and similar problems in maritime transportation..

    Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

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    The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios
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