Real-time truck scheduling model for single inbound and outbound doors cross-dock

Published: 13 September 2023| Version 1 | DOI: 10.17632/bgbspn8bxm.1
Contributors:
Bilge Torbali,

Description

This dataset is in regard to Chapter 4 of the PhD thesis titled "Real-time Truck Scheduling in Cross-Docking: A Hybrid Multi-Agent Simulation Framework". It is organised in 6 folders, each representing a combination of inbound and outbound traffic levels. A folder is named with the following convention: "<I><O>_168h" Where: - <I> represents the inbound traffic level - <O> represents the outbound traffic level - 168h represents the simulation length (all simulations in this dataset span 168 hours) Traffic levels are defined as follow: - H: high traffic, 156 pallets per hour - M: medium traffic, 78 pallets per hour - L: low traffic, 39 pallets per hour For example, the folder "MH_168h" represents medium traffic of inbound trucks (78p/h), high traffic of outbound trucks (156p/h) for a duration of 168h. Each folder contains 10 Excel files, each encompassing one simulation instance input data. Each Excel file contains the following worksheets: - inboundTrucks: list of inbound trucks (one per row) with a unique ID and their corresponding arrival times since start of simulation in minutes. - outboundTrucks: list of outbound trucks (one per row) with a unique ID, their corresponding arrival times since start of simulation in minutes, their due date in minutes since start of simulation and their destination idententified by an integer ranging from 1 to 3 (included). - pallets: list of pallets (one per row) with a unique ID, the ID of the inbound truck in which they start the simulation, their due date in minutes since start of simulation, their destination idententified by an integer ranging from 1 to 3 (included) and their type identified by a letter A, B or C.

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Institutions

Institut Polytechnique de Grenoble, Laboratoire G-SCOP, Universite Grenoble Alpes

Categories

Engineering, Discrete Event Simulation, Agent-Based Modeling, Multi-Agent System

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