A Study on the Container Loading Problem

碩士 === 國立臺灣海洋大學 === 航運管理學系 === 100 === Abstract Container loading problems are important for sea transportation, air transportation and manufacturing. The way adopted to load cargoes into a container has direct impacts on the freight of a supply chain and cost calculation. In order to maximize profi...

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Main Authors: Ting Chao, 趙庭
Other Authors: Dr. Chu Ching -Wu
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/90310433844220342877
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spelling ndltd-TW-100NTOU53010832015-10-13T22:01:08Z http://ndltd.ncl.edu.tw/handle/90310433844220342877 A Study on the Container Loading Problem 貨櫃裝填問題之研究 Ting Chao 趙庭 碩士 國立臺灣海洋大學 航運管理學系 100 Abstract Container loading problems are important for sea transportation, air transportation and manufacturing. The way adopted to load cargoes into a container has direct impacts on the freight of a supply chain and cost calculation. In order to maximize profit, how to load cargoes into a container by minimizing the unused capacity is worthy of a study. In this thesis, we study a container loading problem with multiple types of cargoes. The objective of this thesis is solving the container loading problem within a reasonable time by minimizing the unused capacity. This thesis presents a genetic algorithm for a three dimensional container loading problem. The algorithm can be divided into two stages, construction and improvement stages. In the construction stage, a wall building method is used to calculate the unused space and to decide the loading priority of cargoes and stopping criterion. We keep building a layer within the current wall until no more space available. In order to mi-nimize the wasted space, we modified the wall building method by incorporating the concept of layer determine box. It is achieved by setting the width of each layer equal to layer determine box’s width. In improvement stage, the genetic algorithm is used to load the container by taking the results of the construction stage as an input. Based on chromosome coding, we gen-erate the initial population and there calculate the fitness for further replication, cros-sover, and mutation. 15 test questions from Operations Research Library and a real world data are tested. Computational results show that our algorithm provides and ac-curate and efficient method for solving the container loading problem. Keywords: container loading problem; genetic algorithm; heuristic algorithm Dr. Chu Ching -Wu 朱經武博士 2012 學位論文 ; thesis 76 zh-TW
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description 碩士 === 國立臺灣海洋大學 === 航運管理學系 === 100 === Abstract Container loading problems are important for sea transportation, air transportation and manufacturing. The way adopted to load cargoes into a container has direct impacts on the freight of a supply chain and cost calculation. In order to maximize profit, how to load cargoes into a container by minimizing the unused capacity is worthy of a study. In this thesis, we study a container loading problem with multiple types of cargoes. The objective of this thesis is solving the container loading problem within a reasonable time by minimizing the unused capacity. This thesis presents a genetic algorithm for a three dimensional container loading problem. The algorithm can be divided into two stages, construction and improvement stages. In the construction stage, a wall building method is used to calculate the unused space and to decide the loading priority of cargoes and stopping criterion. We keep building a layer within the current wall until no more space available. In order to mi-nimize the wasted space, we modified the wall building method by incorporating the concept of layer determine box. It is achieved by setting the width of each layer equal to layer determine box’s width. In improvement stage, the genetic algorithm is used to load the container by taking the results of the construction stage as an input. Based on chromosome coding, we gen-erate the initial population and there calculate the fitness for further replication, cros-sover, and mutation. 15 test questions from Operations Research Library and a real world data are tested. Computational results show that our algorithm provides and ac-curate and efficient method for solving the container loading problem. Keywords: container loading problem; genetic algorithm; heuristic algorithm
author2 Dr. Chu Ching -Wu
author_facet Dr. Chu Ching -Wu
Ting Chao
趙庭
author Ting Chao
趙庭
spellingShingle Ting Chao
趙庭
A Study on the Container Loading Problem
author_sort Ting Chao
title A Study on the Container Loading Problem
title_short A Study on the Container Loading Problem
title_full A Study on the Container Loading Problem
title_fullStr A Study on the Container Loading Problem
title_full_unstemmed A Study on the Container Loading Problem
title_sort study on the container loading problem
publishDate 2012
url http://ndltd.ncl.edu.tw/handle/90310433844220342877
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