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Understanding the Impact of User Behaviours and Scheduling Parameters on the Effectiveness of a Terminal Appointment System Using Discrete Event Simulation

Conference paper
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Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 567)

Abstract

This research improves understanding of the impact of specific types of truck driver behaviour and temporal scheduling on the effectiveness of a terminal appointment system. A discrete event simulation model of a bulk cargo marine terminal is developed to analyse parameters related to driver behaviour (punctuality and proportion of planned appointments) and temporal scheduling (appointments per time window and time window spacing) on truck flows and turnaround times at the terminal. The model is based on an Australian wood chip export marine terminal currently experiencing significant truck congestion. The terminal operator and stakeholders have expressed interest in the implementation of an appointment system to address this issue. The modelling presented in this research was used to inform their investigation into developing an appointment system solution.

Simulation results indicate that the proportion of planned appointments, used as a proxy for the appointment system use, has a significant impact on truck turnaround times. Greater truck arrival punctuality only marginally improves truck turnaround times. Interestingly most optimization approaches continue to focus on improving punctuality through service rules or financial penalties in order to achieve optimal turnaround times. However, the additional cost in terms of complexity or assumptions for optimal solutions against non-optimal approaches are rarely weighed in terms of dividends of the marginal improvements generated. By involving terminal users (drivers and transporters) in the design of an appointment system and its scheduling parameters, terminal operators can significantly improve appointment system use and effectiveness by increasing the probability of positive users’ behaviours.

Keywords

Transport management Supply chain collaboration User requirements Congestion management 

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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.ARC Centre for Forest Value, Discipline of ICT, College of Sciences and EngineeringUniversity of TasmaniaHobartAustralia
  2. 2.Centre for Logistics, Department of Materials and ProductionAalborg UniversityAalborgDenmark
  3. 3.Department of Mechanical and Industrial EngineeringNorwegian University of Science and TechnologyTrondheimNorway

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