Solving real-time cross docking truck-to-door assignment and scheduling using mixed integer programming and fuzzy logic model / Wan Nor Ashikin Wan Ahmad Fatthi

Efficiency of cross docking is mainly affected by the inbound operation’s total operation time that involves truck-to-door assignment and scheduling. However, many cross docking centres are still practising conservative way for assigning and scheduling trucks to dock doors. Most current studies addr...

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Main Author: Wan Ahmad Fatthi, Wan Nor Ashikin
Format: Thesis
Language:English
Published: 2014
Online Access:https://ir.uitm.edu.my/id/eprint/16466/2/TM_WAN%20NOR%20ASHIKIN%20WAN%20AHMAD%20FATTHI%20CS%2014_5.pdf
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author Wan Ahmad Fatthi, Wan Nor Ashikin
author_facet Wan Ahmad Fatthi, Wan Nor Ashikin
author_sort Wan Ahmad Fatthi, Wan Nor Ashikin
collection UITM
description Efficiency of cross docking is mainly affected by the inbound operation’s total operation time that involves truck-to-door assignment and scheduling. However, many cross docking centres are still practising conservative way for assigning and scheduling trucks to dock doors. Most current studies addressed deterministic truck scheduling model, thus, unable to deal with real time and dynamic environment of trucks arrival at the cross docking centre. Thus, this study embarks on four objectives which are to identify current issues of cross docking’s truck-to-door assignment and scheduling, to estimate the unloading time of a truck using fuzzy logic modelling, to develop a Mixed Integer Programming (MIP) model that minimizes the total service time of trucks at the inbound operation based on the estimated unloading time; and to analyse the simulations of daily real time truck scheduling operations based on the proposed model. This study utilized data gathered from a third party logistics company (3PL). Results from data analysis were used as basis for establishing the models of this study. Statistical analysis was utilized for hypothesis testing. Monte Carlo simulation experiments using an automated Excel-VBA template were conducted for verification and validation of the models. Based on the results, the developed mathematical model has been proven to be reliable in producing feasible solutions with low waiting time per truck and low service time, thus, capable of minimizing the total service time for all trucks at inbound operation at cross docking centre. The models and findings of this study can be utilized to enhance the cross docking services especially in Malaysia.
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spelling oai:ir.uitm.edu.my:164662022-04-08T07:55:09Z https://ir.uitm.edu.my/id/eprint/16466/ Solving real-time cross docking truck-to-door assignment and scheduling using mixed integer programming and fuzzy logic model / Wan Nor Ashikin Wan Ahmad Fatthi Wan Ahmad Fatthi, Wan Nor Ashikin Efficiency of cross docking is mainly affected by the inbound operation’s total operation time that involves truck-to-door assignment and scheduling. However, many cross docking centres are still practising conservative way for assigning and scheduling trucks to dock doors. Most current studies addressed deterministic truck scheduling model, thus, unable to deal with real time and dynamic environment of trucks arrival at the cross docking centre. Thus, this study embarks on four objectives which are to identify current issues of cross docking’s truck-to-door assignment and scheduling, to estimate the unloading time of a truck using fuzzy logic modelling, to develop a Mixed Integer Programming (MIP) model that minimizes the total service time of trucks at the inbound operation based on the estimated unloading time; and to analyse the simulations of daily real time truck scheduling operations based on the proposed model. This study utilized data gathered from a third party logistics company (3PL). Results from data analysis were used as basis for establishing the models of this study. Statistical analysis was utilized for hypothesis testing. Monte Carlo simulation experiments using an automated Excel-VBA template were conducted for verification and validation of the models. Based on the results, the developed mathematical model has been proven to be reliable in producing feasible solutions with low waiting time per truck and low service time, thus, capable of minimizing the total service time for all trucks at inbound operation at cross docking centre. The models and findings of this study can be utilized to enhance the cross docking services especially in Malaysia. 2014-04 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/16466/2/TM_WAN%20NOR%20ASHIKIN%20WAN%20AHMAD%20FATTHI%20CS%2014_5.pdf Solving real-time cross docking truck-to-door assignment and scheduling using mixed integer programming and fuzzy logic model / Wan Nor Ashikin Wan Ahmad Fatthi. (2014) Masters thesis, thesis, Universiti Teknologi MARA. <http://terminalib.uitm.edu.my/16466.pdf>
spellingShingle Wan Ahmad Fatthi, Wan Nor Ashikin
Solving real-time cross docking truck-to-door assignment and scheduling using mixed integer programming and fuzzy logic model / Wan Nor Ashikin Wan Ahmad Fatthi
title Solving real-time cross docking truck-to-door assignment and scheduling using mixed integer programming and fuzzy logic model / Wan Nor Ashikin Wan Ahmad Fatthi
title_full Solving real-time cross docking truck-to-door assignment and scheduling using mixed integer programming and fuzzy logic model / Wan Nor Ashikin Wan Ahmad Fatthi
title_fullStr Solving real-time cross docking truck-to-door assignment and scheduling using mixed integer programming and fuzzy logic model / Wan Nor Ashikin Wan Ahmad Fatthi
title_full_unstemmed Solving real-time cross docking truck-to-door assignment and scheduling using mixed integer programming and fuzzy logic model / Wan Nor Ashikin Wan Ahmad Fatthi
title_short Solving real-time cross docking truck-to-door assignment and scheduling using mixed integer programming and fuzzy logic model / Wan Nor Ashikin Wan Ahmad Fatthi
title_sort solving real time cross docking truck to door assignment and scheduling using mixed integer programming and fuzzy logic model wan nor ashikin wan ahmad fatthi
url https://ir.uitm.edu.my/id/eprint/16466/2/TM_WAN%20NOR%20ASHIKIN%20WAN%20AHMAD%20FATTHI%20CS%2014_5.pdf
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