Optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem

Efficient arrangement of cargo in logistics is crucial in minimizing the operational cost and it can be a complex task as it involves multiple constraints like cargo with various volumes and weights. Therefore, manual cargo arrangement is challenging, especially when the types of cargo and numbers o...

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Main Author:	Jie, Zhou
Format:	Thesis
Language:	English
Published:	2021
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/99511/1/ZhouJieMKE2021.pdf
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id	my-utm-ep.99511
record_format	uketd_dc
spelling	my-utm-ep.995112023-02-27T08:05:18Z Optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem 2021 Jie, Zhou TK Electrical engineering. Electronics Nuclear engineering Efficient arrangement of cargo in logistics is crucial in minimizing the operational cost and it can be a complex task as it involves multiple constraints like cargo with various volumes and weights. Therefore, manual cargo arrangement is challenging, especially when the types of cargo and numbers of customer’s increase. Cargo arrangement is categorized as a problem that involves mathematical models and efficient optimization algorithms. This project proposes a multi-objective, multiconstraint mathematical model for the three-dimensional optimization problem (3- DOP), with constraints such as packaging volume, weight and quantity of different cargo types. The requirements and characteristics of the container are also considered in establishing the proposed model to achieve the loading optimization objectives of maximizing the utilization and capacity of container space. This project uses genetic algorithm (GA) as the global search properties to obtain the optimal solution. The proposed model comprised of an objective function and a set of constraints in cargo loading such as weight, rotation, overlapping and stacking constraints. The real coded methods of GA, optimal preservation strategy and Pareto front are introduced. Subsequently, a GA is developed using MATLAB software. The cargo sizes of different transport companies are used as test samples. The maximum space utilization is achieved up to 77.59%, and the weight maximum is 58.12%. Nevertheless, it is observed that an increase in the number of constraints has a significant effect on the optimization. In short, the effectiveness of the proposed optimization algorithm is verified. 2021 Thesis http://eprints.utm.my/id/eprint/99511/ http://eprints.utm.my/id/eprint/99511/1/ZhouJieMKE2021.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:149882 masters Universiti Teknologi Malaysia Faculty of Engineering - School of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Jie, Zhou Optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem
description	Efficient arrangement of cargo in logistics is crucial in minimizing the operational cost and it can be a complex task as it involves multiple constraints like cargo with various volumes and weights. Therefore, manual cargo arrangement is challenging, especially when the types of cargo and numbers of customer’s increase. Cargo arrangement is categorized as a problem that involves mathematical models and efficient optimization algorithms. This project proposes a multi-objective, multiconstraint mathematical model for the three-dimensional optimization problem (3- DOP), with constraints such as packaging volume, weight and quantity of different cargo types. The requirements and characteristics of the container are also considered in establishing the proposed model to achieve the loading optimization objectives of maximizing the utilization and capacity of container space. This project uses genetic algorithm (GA) as the global search properties to obtain the optimal solution. The proposed model comprised of an objective function and a set of constraints in cargo loading such as weight, rotation, overlapping and stacking constraints. The real coded methods of GA, optimal preservation strategy and Pareto front are introduced. Subsequently, a GA is developed using MATLAB software. The cargo sizes of different transport companies are used as test samples. The maximum space utilization is achieved up to 77.59%, and the weight maximum is 58.12%. Nevertheless, it is observed that an increase in the number of constraints has a significant effect on the optimization. In short, the effectiveness of the proposed optimization algorithm is verified.
format	Thesis
qualification_level	Master's degree
author	Jie, Zhou
author_facet	Jie, Zhou
author_sort	Jie, Zhou
title	Optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem
title_short	Optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem
title_full	Optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem
title_fullStr	Optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem
title_full_unstemmed	Optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem
title_sort	optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem
granting_institution	Universiti Teknologi Malaysia
granting_department	Faculty of Engineering - School of Electrical Engineering
publishDate	2021
url	http://eprints.utm.my/id/eprint/99511/1/ZhouJieMKE2021.pdf
_version_	1776100608417202176

Optimization model with multiple constraints using genetic algorithm method for cargo arrangement problem

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