Bi-objective Recoverable Berth Allocation and Quay Crane Assignment Planning under Environmental Uncertainty

This study discusses the development of tactical-level integrated planning at seaport container terminals in an uncertain environment. The suggested approach seeks to strike a balance between the cost-effectiveness of a robust baseline schedule and recovery plan and the required quality of customer service in order to enhance the competitive edge of container ports. Integrated planning for a tactical level at the container terminal synchronizes the decisions of berth allocation and quay crane assignment planning by taking into account the unpredictability of the vessel's arrival time and handling time caused by a variety of unforeseen factors such as unfavorable weather conditions, instability in the productivity rate of the quay cranes, the uncertainty of the quantity of loading and discharging containers, and other unpredictable events. The proposed optimization model produces a robust and proactive baseline schedule with a recoverable reactive plan for each scenario that occurs by utilizing buffer times and quay cranes that anticipate fluctuations in uncertain parameters. The proposed bi-objective recoverable robustness optimization model is solved by applying a hybrid method, namely the Rolling Horizon-based Optimization Algorithm (RHOA) and the Preemptive Goal Programming approach, using Gurobi-Python Optimization. The proposed bi-objective recoverable robust optimization model demonstrates superior solution quality in terms of service level and total costs, as well as a more efficient computational time when compared to an optimization model that minimizes total costs for tactical level planning decisions in seaside container terminals

Future Greener Seaports:A Review of New Infrastructure, Challenges, and Energy Efficiency Measures

Recently, the application of renewable energy sources (RESs) for power distribution systems is growing immensely. This advancement brings several advantages, such as energy sustainability and reliability, easier maintenance, cost-effective energy sources, and ecofriendly. The application of RESs in maritime systems such as port microgrids massively improves energy efficiency and reduces the utilization of fossil fuels, which is a serious threat to the environment. Accordingly, ports are receiving several initiatives to improve their energy efficiency by deploying different types of RESs based on the power electronic converters. This paper conducts a systematic review to provide cutting-edge state-of-the-art on the modern electrification and infrastructure of seaports taking into account some challenges such as the environmental aspects, energy efficiency enhancement, renewable energy integration, and legislative and regulatory requirements. Moreover, the technological methods, including electrifications, digitalization, onshore power supply applications, and energy storage systems of ports, are addressed. Furthermore, details of some operational strategies such as energy-aware operations and peak-shaving are delivered. Besides, the infrastructure scheme to enhance the energy efficiency of modern ports, including port microgrids and seaport smart microgrids are delivered. Finally, the applications of nascent technologies in seaports are presented

Evaluasi Aturan Penugasan Dan Penentuan Jumlah Crane Pada Pt Terminal Petikemas Surabaya

PT Terminal Petikemas Surabaya (TPS) bergerak di bidang penyediaan fasilitas terminal petikemas bagi pelaku usaha di wilayah Indonesia Timur. Salah satu visi PT TPS adalah menyediakan dan memastikan bahwa layanan yang diberikan kepada para pelanggan tepat waktu dan terjadwal. Untuk mendukung visi tersebut, perusahaan terus berusaha meningkatkan layanan dalam hal waktu bongkar muat. Berdasarkan data pada periode observasi, diketahui bahwa terdapat beberapa berth yang masih memiliki nilai BSH (Boxes Ships Hours) di bawah target perusahaan. Untuk meningkatkan nilai BSH, maka dibutuhkan suatu solusi dengan cara mempersingkat total waktu kerja crane. Penentuan alokasi crane akan berpengaruh terhadap waktu pelayanan bongkar muat pada suatu kapal, sehingga pada penelitian ini akan dilakukan evaluasi aturan alokasi crane pada kapal untuk melihat dampak aturan penugasan crane terhadap waktu kerja crane pada tiap kapal di tiap berth. Penelitian ini bertujuan untuk melakukan evaluasi terhadap kondisi eksisting untuk setiap berth dan setiap crane, mengetahui aturan pengalokasian crane pada tiap kapal pada kondisi eksisting, dan mengembangkan skenario perbaikan berupa alternatif aturan penugasan crane pada tiap kapal di tiap berth. Metode yang digunakan adalah simulasi dengan skenario perbaikan berupa perubahan jumlah maksimal crane yang dialokasikan pada tiap berth. Skenario terpilih merupakan skenario yang menghasilkan rata-rata waktu kerja crane di berth terkecil ====================================================================== PT Terminal Petikemas Surabaya (TPS) provides container terminal facilities for the traders at the eastern regions of Indonesia. One of the vision of PT TPS is to give and ensure the services on time for its customers. In order to support their vision, PT TPS has to improve their services by doing loading and discharging container on time. Based on the data in observation period, there are some ships that had the BSH (Boxes Ships Hours) value below the target. In order to increase the BSH value, it needed a way to shorten the vessel service time. Crane allocation will affect the vessel service time. In this study, crane allocation rules will be evaluated to see the impact of the crane assignment rule to crane working time on each vessel at each berth. This study aims to evaluate the existing conditions, identify the crane allocation rules, and develop scenarios i.e the alternative of the crane assignment rules for each berth and each crane. The method used is the simulation with software Arena. In this study, the maximum number of crane that allocated on each vessel will be changed. The chosen scenario is the scenario that generates the smallest average of crane working time in each bert

Barge Prioritization, Assignment, and Scheduling During Inland Waterway Disruption Responses

Inland waterways face natural and man-made disruptions that may affect navigation and infrastructure operations leading to barge traffic disruptions and economic losses. This dissertation investigates inland waterway disruption responses to intelligently redirect disrupted barges to inland terminals and prioritize offloading while minimizing total cargo value loss. This problem is known in the literature as the cargo prioritization and terminal allocation problem (CPTAP). A previous study formulated the CPTAP as a non-linear integer programming (NLIP) model solved with a genetic algorithm (GA) approach. This dissertation contributes three new and improved approaches to solve the CPTAP. The first approach is a decomposition based sequential heuristic (DBSH) that reduces the time to obtain a response solution by decomposing the CPTAP into separate cargo prioritization, assignment, and scheduling subproblems. The DBSH integrates the Analytic Hierarchy Process and linear programming to prioritize cargo and allocate barges to terminals. Our findings show that compared to the GA approach, the DBSH is more suited to solve large sized decision problems resulting in similar or reduced cargo value loss and drastically improved computational time. The second approach formulates CPTAP as a mixed integer linear programming (MILP) model improved through the addition of valid inequalities (MILP\u27). Due to the complexity of the NLIP, the GA results were validated only for small size instances. This dissertation fills this gap by using the lower bounds of the MILP\u27 model to validate the quality of all prior GA solutions. In addition, a comparison of the MILP\u27 and GA solutions for several real world scenarios show that the MILP\u27 formulation outperforms the NLIP model solved with the GA approach by reducing the total cargo value loss objective. The third approach reformulates the MILP model via Dantzig-Wolfe decomposition and develops an exact method based on branch-and-price technique to solve the model. Previous approaches obtained optimal solutions for instances of the CPTAP that consist of up to five terminals and nine barges. The main contribution of this new approach is the ability to obtain optimal solutions of larger CPTAP instances involving up to ten terminals and thirty barges in reasonable computational time

The synergistic effect of operational research and big data analytics in greening container terminal operations: a review and future directions

Container Terminals (CTs) are continuously presented with highly interrelated, complex, and uncertain planning tasks. The ever-increasing intensity of operations at CTs in recent years has also resulted in increasing environmental concerns, and they are experiencing an unprecedented pressure to lower their emissions. Operational Research (OR), as a key player in the optimisation of the complex decision problems that arise from the quay and land side operations at CTs, has been therefore presented with new challenges and opportunities to incorporate environmental considerations into decision making and better utilise the ‘big data’ that is continuously generated from the never-stopping operations at CTs. The state-of-the-art literature on OR's incorporation of environmental considerations and its interplay with Big Data Analytics (BDA) is, however, still very much underdeveloped, fragmented, and divergent, and a guiding framework is completely missing. This paper presents a review of the most relevant developments in the field and sheds light on promising research opportunities for the better exploitation of the synergistic effect of the two disciplines in addressing CT operational problems, while incorporating uncertainty and environmental concerns efficiently. The paper finds that while OR has thus far contributed to improving the environmental performance of CTs (rather implicitly), this can be much further stepped up with more explicit incorporation of environmental considerations and better exploitation of BDA predictive modelling capabilities. New interdisciplinary research at the intersection of conventional CT optimisation problems, energy management and sizing, and net-zero technology and energy vectors adoption is also presented as a prominent line of future research