A simulation-based optimization approach for external trucks appointment scheduling in container terminals

Ahmed Azab, Ahmed Karam Abdelfattah Mostafa, Amr Eltawil

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

In Container Terminals (CTs), many containers are daily delivered by a large number of External Trucks (ETs) which lead to several issues such as long waiting times at gates and yards, harmful emissions, and low productivity of the CTs. To resolve these issues, truck appointment systems are used to schedule appointments of ETs and achieve more balance in CTs’ workload. Most of the studies have focused on deterministic modelling of the ETs’ arrival process with considering yard operations or gate operations. Also, a little effort has been devoted to collaboration between trucking companies and CTs when scheduling ETs’ appointments. Unlike previous studies, this paper presents a simulation-based optimization approach to collaboratively schedule ETs’ appointments with considering yard and gate operations as well as their stochastic natures. The proposed approach integrates a simulation model with an MIP model with objective of minimizing turnaround times of ETs and inconveniences resulting from shifting the arrivals of ETs away from their preferred arrival times. The proposed approach is validated against an approach from literature. In addition, its performance is investigated by solving artificial instances inspired by real data. A framework for implementing the proposed system in the IoT-based container terminals is also developed.

Original languageEnglish
JournalInternational Journal of Modelling & Simulation
ISSN0228-6203
DOIs
Publication statusPublished - 2 May 2019

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Simulation-based Optimization
Container Terminal
Trucks
Containers
Scheduling
Schedule
Arrival Time
Container
Waiting Time
Productivity
Workload
Resolve
Simulation Model
Turnaround time
Integrate
Modeling

Cite this

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title = "A simulation-based optimization approach for external trucks appointment scheduling in container terminals",
abstract = "In Container Terminals (CTs), many containers are daily delivered by a large number of External Trucks (ETs) which lead to several issues such as long waiting times at gates and yards, harmful emissions, and low productivity of the CTs. To resolve these issues, truck appointment systems are used to schedule appointments of ETs and achieve more balance in CTs’ workload. Most of the studies have focused on deterministic modelling of the ETs’ arrival process with considering yard operations or gate operations. Also, a little effort has been devoted to collaboration between trucking companies and CTs when scheduling ETs’ appointments. Unlike previous studies, this paper presents a simulation-based optimization approach to collaboratively schedule ETs’ appointments with considering yard and gate operations as well as their stochastic natures. The proposed approach integrates a simulation model with an MIP model with objective of minimizing turnaround times of ETs and inconveniences resulting from shifting the arrivals of ETs away from their preferred arrival times. The proposed approach is validated against an approach from literature. In addition, its performance is investigated by solving artificial instances inspired by real data. A framework for implementing the proposed system in the IoT-based container terminals is also developed.",
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A simulation-based optimization approach for external trucks appointment scheduling in container terminals. / Azab, Ahmed; Mostafa, Ahmed Karam Abdelfattah; Eltawil, Amr.

In: International Journal of Modelling & Simulation, 02.05.2019.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

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AU - Mostafa, Ahmed Karam Abdelfattah

AU - Eltawil, Amr

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N2 - In Container Terminals (CTs), many containers are daily delivered by a large number of External Trucks (ETs) which lead to several issues such as long waiting times at gates and yards, harmful emissions, and low productivity of the CTs. To resolve these issues, truck appointment systems are used to schedule appointments of ETs and achieve more balance in CTs’ workload. Most of the studies have focused on deterministic modelling of the ETs’ arrival process with considering yard operations or gate operations. Also, a little effort has been devoted to collaboration between trucking companies and CTs when scheduling ETs’ appointments. Unlike previous studies, this paper presents a simulation-based optimization approach to collaboratively schedule ETs’ appointments with considering yard and gate operations as well as their stochastic natures. The proposed approach integrates a simulation model with an MIP model with objective of minimizing turnaround times of ETs and inconveniences resulting from shifting the arrivals of ETs away from their preferred arrival times. The proposed approach is validated against an approach from literature. In addition, its performance is investigated by solving artificial instances inspired by real data. A framework for implementing the proposed system in the IoT-based container terminals is also developed.

AB - In Container Terminals (CTs), many containers are daily delivered by a large number of External Trucks (ETs) which lead to several issues such as long waiting times at gates and yards, harmful emissions, and low productivity of the CTs. To resolve these issues, truck appointment systems are used to schedule appointments of ETs and achieve more balance in CTs’ workload. Most of the studies have focused on deterministic modelling of the ETs’ arrival process with considering yard operations or gate operations. Also, a little effort has been devoted to collaboration between trucking companies and CTs when scheduling ETs’ appointments. Unlike previous studies, this paper presents a simulation-based optimization approach to collaboratively schedule ETs’ appointments with considering yard and gate operations as well as their stochastic natures. The proposed approach integrates a simulation model with an MIP model with objective of minimizing turnaround times of ETs and inconveniences resulting from shifting the arrivals of ETs away from their preferred arrival times. The proposed approach is validated against an approach from literature. In addition, its performance is investigated by solving artificial instances inspired by real data. A framework for implementing the proposed system in the IoT-based container terminals is also developed.

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