A decision support system for quayside operations in a container terminal

Ursavas, Evrim

doi:10.1016/j.dss.2014.01.003

Cited by 41 publications

(21 citation statements)

References 22 publications

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“…Economic -721-Intangible Capital -https://doi.org/10. 3926/ic.956 instabilities have enhanced the need to reduce costs and increase the level of service quality, which has led to greater complexity of the relevant supply chains (Ursavas, 2014). …”

Section: Introductionmentioning

confidence: 99%

Knowledge construction about port performance evaluation: An international literature analysis

Somensi

Ensslin

Dutra

et al. 2017

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Purpose: This study aims to identify and analyze the characteristics of international scientific research that addresses the segment of literature referring to port performance evaluation, in order to identify the existence of a theoretical alignment between the concept of performance evaluation, as an area of knowledge, and the practical application of port performance evaluation.Design/methodology: For the approach to the problem, this paper makes use of qualitative research, analyzing bibliographical portfolio characteristics related to port performance evaluation. An action research strategy was adopted, according to which the authors selected the bibliographical portfolio based on analysis and interpretation.

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Section: Introductionmentioning

confidence: 99%

Knowledge construction about port performance evaluation: An international literature analysis

Somensi

Ensslin

Dutra

et al. 2017

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“…Murty et al, 2005;Ngai et al, 2007;Ursavas, 2014). Ursavas (2014) also mentions some works in literature that have proposed DSSs for container transportation problems. Some studies consider that demand is known in advance, such as Shen and Khoong (1995), who developed a mathematical model for planning the distribution of empty containers, suggesting specific options to the decision maker.…”

Section: Optimisation Models For Decision Problemsmentioning

confidence: 97%

“…Several DSSs have been developed that focus on the operational problem of container transhipment in container terminals (e.g. Murty et al, 2005;Ngai et al, 2007;Ursavas, 2014). Ursavas (2014) also mentions some works in literature that have proposed DSSs for container transportation problems.…”

Section: Optimisation Models For Decision Problemsmentioning

confidence: 99%

Real-time container transport planning with decision trees based on offline obtained optimal solutions

Riessen

Negenborn

Dekker

2016

Decision Support Systems

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Hinterland networks for container transportation require planning methods in order to increase efficiency and reliability of the inland road, rail and waterway connections. In this paper we aim to derive real-time decision rules for suitable allocations of containers to inland services by analysing the solution structure of a centralised optimisation method used offline on historic data. The decision tree can be used in a decision support system (DSS) for instantaneously allocating incoming orders to suitable services, without the need for continuous planning updates. Such a DSS is beneficial, as it is easy to implement in the current practice of container transportation. Earlier proposed centralised methods can find the optimal solution for the intermodal inland transportation problem in retrospect, but are not suitable when information becomes gradually available. The main contributions are threefold: firstly, a structured method for creating decision trees from optimal solutions is proposed. Secondly, an innovative method is used for obtaining multiple equivalent optimal solutions to prevent overfitting of the decision tree. And finally, a structured analysis of three error types is presented for assessing the quality of an obtained tree. A case study illustrates the method's purpose by comparing the quality of the resulting plan with alternative methods.

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“…It is worth noting that strategies for the QC assignments include time-invariant QC assignments, time-variant QC assignments, and limited time-variant QC assignments. Time-invariant QC assignments imply that the number of QCs serving each vessel must be the same during the service of the vessel [16,34], while time-variant QC assignments imply that the number of QCs can be varied dynamically according to the assignable range of QCs allowed for the vessel [12,15,17]. Note that varying the number of QCs serving the vessel is sometimes essential for improving the utilization of QCs as well as the service times of vessels.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…There is a tight interrelation between the BAP, the QCAP, and the ITAP [14]. Existing studies have mostly focused on combining the BAP and the QCAP into a unified model called the integrated berth allocation and crane assignment problem (BACAP) [12,[15][16][17]. For a detailed review on BACAP studies, we refer the readers to the recent survey in Reference [5].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient and Integrated Allocation of Berths, Quay Cranes, and Internal Trucks in Container Terminals

2020

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Despite a significant number of studies that have focused on the operational efficiency of container terminals, existing literature has paid little attention to improving energy efficiency, e.g., energy consumption and negative externalities in container terminals. Most researchers consider energy-saving goals when allocating berths and quay cranes to vessels, assuming that internal trucks are in sufficient supply. Furthermore, recent studies have revealed that shortage of internal trucks has become an issue that greatly affects the operational and energy efficiencies of container terminals. This work presents a planning model that integrates berth allocation, quay crane assignment, and internal truck assignment problems. The developed model contributes to existing literature by including energy-saving goals in the integrated planning of these problems, as well as including important realistic factors such as shortages of internal trucks and handling time estimations, thus producing a reliable handling plan that achieves energy and cost savings without additional truck investment. To solve realistic problems, a Lagrangian relaxation-based method is developed. Furthermore, the benefits of the developed approach are demonstrated by comparing it to an existing approach. On average, our approach could improve the solutions of the integrated problem with different numbers of internal trucks by 6% compared to the solutions obtained using the existing approach.

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A decision support system for quayside operations in a container terminal

Cited by 41 publications

References 22 publications

Knowledge construction about port performance evaluation: An international literature analysis

Knowledge construction about port performance evaluation: An international literature analysis

Real-time container transport planning with decision trees based on offline obtained optimal solutions

Energy-Efficient and Integrated Allocation of Berths, Quay Cranes, and Internal Trucks in Container Terminals

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