---
title: Flexible Truck Appointment System
url: https://www.ml-quant.com/papers/repec/ids-ijlsma-v-48-y-2024-i-2-p-244-266/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:ids:ijlsma:v:48:y:2024:i:2:p:244-266
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.inderscience.com%2Flink.php%3Fid%3D139958%3Bh%3Drepec%3Aids%3Aijlsma%3Av%3A48%3Ay%3A2024%3Ai%3A2%3Ap%3A244-266
featured: 2024-07-31
citations: unknown
topic: ML & AI Methods
---


# Flexible Truck Appointment System

The paper proposes a machine learning model for flexible truck appointment systems in smart ports, using real-time data to identify disruptions and reschedule appointments, thus enhancing port efficiency.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.inderscience.com%2Flink.php%3Fid%3D139958%3Bh%3Drepec%3Aids%3Aijlsma%3Av%3A48%3Ay%3A2024%3Ai%3A2%3Ap%3A244-266
- Identifier: RePEc:ids:ijlsma:v:48:y:2024:i:2:p:244-266
- Released: 2024-07-31
- First featured: Quant Letter No. 59 (2024-07-31): https://www.ml-quant.com/issues/2024-07-31/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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