以改良式基因演算法進行整合組裝規劃與機器佈置之生產系統設計

Developing an Improved Genetic Algorithm for the Production System Design with Assembly Planning and Machine Layout

江宏鵬(Hung-peng Chiang)

指導教授 ： 王河星

國立臺北科技大學/管理學院/工業工程與管理研究所/碩士(2009年)

摘要

本研究主要針對生產系統中常見的兩個規劃議題－組裝作業規劃與機器佈置進行整合，並依據此整合性議題建構一最佳化數學模式。透過此規劃模式將可見生產系統具最小的循環時間及產線最小的機器總閒置時間。此外，為能有效地進行數學模式求解，本研究提出一多親代改良式基因演算法(Multi-parent Improvement Genetic Algorithm, MpI-GA)。MpI-GA以每張訂單作業數為基，依序將各作業指派至能夠處理作業之機器，並以多親代方式進行交配作業，以期望能於短時間內獲得一良好的規劃方案。最後將本研究提出的兩個實驗案例使用MpI-GA及GA進行求解，分析結果顯示本研究提出之MpI-GA於此整合性生產系統規劃問題中能獲得穩定且良好的求解品質。

關鍵字

組裝規劃 ； 機器佈置 ； 多親代再組 ； 基因演算法

並列摘要

For a production system that incorporates Assembly Planning and Machine Layout which often are investigated. This research constructs an optimal mathematical model. Its object is to minimize cycle time of each order and minimize total idle time of the production line. Besides, this research offers a Multi-parent Improvement Genetic Algorithm (MpI-GA) to solve the mathematical model effectively. Based on operations of order, MpI-GA determines operation assignment in turn. It also calculates multi-parent crossover that is expected to gain a better planning in a short time. In conclusive, this research compares MpI-GA with traditional Genetic Algorithms (GA) using two designed experiments. The experimental results demonstrate effectiveness of proposed MpI-GA in designing production system.

並列關鍵字

Assembly Planning ； Machine Layout ； Multi-parent Recombination ； Genetic Algorithm

參考文獻

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