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基於遺傳演算法之具有多模具限制的並行機台排程方法 = Parallel ...

國立高雄大學資訊工程學系碩士班

基於遺傳演算法之具有多模具限制的並行機台排程方法 = Parallel Machines Scheduling with Multiple Mold Constraints Based on Genetic Algorithms

紀錄類型:	書目-語言資料,印刷品 : 單行本
並列題名:	Parallel Machines Scheduling with Multiple Mold Constraints Based on Genetic Algorithms
作者:	漆慶福,
其他團體作者:	國立高雄大學
出版地:	高雄市
出版者:	撰者;
出版年:	民102[2013]
面頁冊數:	69面圖，表格 : 30公分;
標題:	排程
標題:	Scheduling
電子資源:	http://hdl.handle.net/11296/ndltd/23538190189799192466
附註:	106年10月31日公開
附註:	參考書目：面64-69
摘要註:	目前要求排程問題之最優解已普遍被認定是NP-hard的問題，因此最近許多學者使用遺傳演算法尋找排程近似最優解，其中許多人已經在效率和質量上找到可以接受的結果。在這項研究中，我們將討論分配在多個並行機器的工作與模具限制的調度問題。每個作業須限制一種工作模具在一部機器上執行，每部機器限制可使用的工作模具，每付模具的數量有限制。此外，每部機器第一份工作開始或機器因改變工作而更換模具時，必須考慮模具安裝時間。因此本文使用遺傳演算法處理上述機器排程問題。其中，使用基因染色體表示機器與模具的排程架構，進而生成一個群體。使用調整運算子，調整機器與模具的衝突，產生可用的排程及提高適應值。染色體交配使用雙點交叉重現新一代染色體。此外，使用反向突變和對換突變 2 種突變操作，防止基因演化陷入局部最優解。程式最後滿足一定世代演化以獲得最好的完工時間排程結果。從實驗結果，驗證了本文提供的演算法之有效性。 Finding optimal solutions of scheduling problems has generally been NP-hard. Recently, GA-based algorithms have been introduced to find nearly optimal solutions, and many of them have found acceptable results in both efficiency and quality. In this study, we discuss the scheduling problem of assigning jobs on multiple parallel machines with mold constraints. The mold constraint specifies that each job needs to be processed with specific molds on a machine and there is an arbitrary amount for each type of molds. Besides, different machines can mount different molds. Setup time is also considered when a first job in a machine starts or when a machine changes molds. A GA-based scheduling algorithm is thus proposed for dealing with the above scheduling problem. In the proposed scheduling approach, a chromosome-generating procedure is designed to generate a population. The adjustment operators are then adopted for improving the fitness values and keeping them from conflict. A two-point crossover operator is adopted to reproduce the new generation of chromosomes. Moreover, two mutation operators, the reverse mutation and the swapping mutation, are used to prevent the solutions from trapping into the local optimum. The scheduling result with the best makespan is then outputted from the population when the terminal condition is met. Finally, experimental results are given to verify the effectiveness of the proposed algorithm.

基於遺傳演算法之具有多模具限制的並行機台排程方法 = Parallel Machines Scheduling with Multiple Mold Constraints Based on Genetic Algorithms
漆, 慶福

基於遺傳演算法之具有多模具限制的並行機台排程方法 = Parallel Machines Scheduling with Multiple Mold Constraints Based on Genetic Algorithms / 漆慶福撰 - 高雄市 : 撰者, 民102[2013]. - 69面 ; 圖，表格 ; 30公分.
106年10月31日公開參考書目：面64-69.
排程Scheduling

基於遺傳演算法之具有多模具限制的並行機台排程方法 = Parallel Machines Scheduling with Multiple Mold Constraints Based on Genetic Algorithms
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