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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my-uitm-ir.164662022-04-08T07:55:09Z 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 2014-04 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 https://ir.uitm.edu.my/id/eprint/16466/ https://ir.uitm.edu.my/id/eprint/16466/2/TM_WAN%20NOR%20ASHIKIN%20WAN%20AHMAD%20FATTHI%20CS%2014_5.pdf text en public mphil masters Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences Shuib, Adibah (Assoc. Prof. Dr.) Mohd Dom, Rosma (Assoc. Prof. Dr.) |
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Universiti Teknologi MARA |
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UiTM Institutional Repository |
language |
English |
advisor |
Shuib, Adibah (Assoc. Prof. Dr.) Mohd Dom, Rosma (Assoc. Prof. Dr.) |
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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Thesis |
qualification_name |
Master of Philosophy (M.Phil.) |
qualification_level |
Master's degree |
author |
Wan Ahmad Fatthi, Wan Nor Ashikin |
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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 |
author_facet |
Wan Ahmad Fatthi, Wan Nor Ashikin |
author_sort |
Wan Ahmad Fatthi, Wan Nor Ashikin |
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_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_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_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 |
granting_institution |
Universiti Teknologi MARA |
granting_department |
Faculty of Computer and Mathematical Sciences |
publishDate |
2014 |
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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