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作者姓名(中文):劉嘉媜
作者姓名(英文):Chia-Chen Liu
論文名稱(中文):成衣業訂單分碼規劃:基於基因遺傳之演算法
論文名稱(外文):Cut Order Planning in Apparel Industry : GA based Heuristics
指導教授姓名(中文):曹譽鐘
指導教授姓名(英文):Yu-Chung Tsao
口試委員姓名(中文):曹譽鐘
王孔政
郭伯勳
口試委員姓名(英文):Yu-Chung Tsao
Kung-Jeng Wang
Po-Hsun Kuo
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:工業管理系
學號:m10601203
出版年(民國):108
畢業學年度:107
學期:2
語文別:英文
論文頁數:46
中文關鍵詞:訂單分碼規劃成衣業基因遺傳演算法啟發式
外文關鍵詞:cut order planningapparel industrygenetic algorithmheuristic
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近年來,大眾對於服飾的需求逐漸增加,製造商必須快速地生產不同種類的服飾吸引顧客。訂單分碼規劃(COP)在成衣業中是被重視的問題之一,如果能夠將各種尺寸之需求量妥善安排在不同模板中,將會降低布料浪費以減少成本。訂單分碼規劃(COP)著重於在模板的長度、寬度和高度皆受到切割設備及切割台的限制下,找尋各種尺寸在模板中之合適組合。
本文提出了一種基於基因遺傳演算法的啟發式,其目的為在滿足需求量的情況下,找出最佳的模板組合並盡可能地減少耗費布料之總長度。首先採用我們提出的啟發式所獲得之可行解作為基因遺傳演算法之初始解,接著使用基因遺傳演算法優化初始解以找尋最佳模板組合。有別於以往大部分的文獻考慮設置、材料及設備等成本,我們只考量布料耗費的總長度。此外,我們將應用本文所提出的方法所產生之結果與其他文獻進行比較,研究結果顯示,本文所提出的方法相較於其他文獻中提出的方法具有更好的表現。
In recent years, the demand for garments has gradually increased and the manufacturers must produce garments rapidly in order to attract customers. Cut order planning (COP) is one of the most important issue in the apparel industry. If there is an appropriate stencils arrangement, it may cut down the cost and fabric wastage. The problem focuses on determining the size combination of a pattern which is subject to the length of cutting table, width, demand orders, and the height of cutting equipment.
This paper presents a Lite Heuristic with Genetic Algorithm (GA) to figure out the COP problem where the objective is to find the optimal combination of stencils to meet to fulfill the demand requirement and minimize the total length. We first apply Lite Heuristic to produce a feasible initial solution of GA in the first stage, and then use GA to yield the optimal feasible solution. Instead of revolving around the setup cost, material cost and so on, we merely consider the fabric length. Additionally, we compare the results with other literature. The results show that our proposed method has better performance than the methodology proposed in other literature.
摘要
ABSTRACT
ACKNOWLEDGEMENT
CONTENTS
LIST OF FIGURE
LIST OF TABLE
CHAPTER 1 INTRODUCTION
1.1 Background and Motivation
1.2 Research Objective
1.3 Research Organization
CHAPTER 2 LITERATURE REVIEW
2.1 Cut Order Planning (COP)
2.2 Heuristics for COP
2.3 Genetic Algorithm (GA)
CHAPTER 3 MODEL FORMULATION
3.1 Problem definition
3.2 Lite Heuristic
3.3 GA
3.3.1 Parent selection
3.3.2 Uniform crossover
3.3.3 Single-point mutation
CHAPTER 4 NUMERICAL STUDY
4.1 A Numerical Example
4.2 Experimental results of Lite Heuristic
4.3 In comparison with other literature
CHAPTER 5 CONCLUSION
5.1 Conclusion
5.2 Future Research
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全文檔公開日期:2024/06/13 (本校及校內區域網路)
全文檔公開日期:不公開 (校外網際網路)
全文檔公開日期:不公開 (國家圖書館:臺灣博碩士論文系統)
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