臺灣博碩士論文加值系統

過去在產品設計時，通常只以公司角度考量，然而，在講求顧客關係管理的現在，更應該重視顧客需求，考量顧客的價值。因此，本研究運用以人為基遺傳演算法(Human Based Genetic Algorithm, HBGA)的智慧代理人特性，透過系統演化出新的產品，以增加新產品上市的成功率。本研究設計三個模組，分別為創意發想模組、產品設計模組，和群體決策類AHP (AHP-Like)概念評估模組。在產品設計階段，本研究設計三個實驗：IGA實驗、HBGA實驗和單一HBGA實驗，以系統傢俱產業的電視櫃組合設計為個案，藉以驗證HBGA可改善IGA(Interactive Genetic Algorithm)人類疲勞的問題，較快求得消費者的滿意解，以及達到群體決策的功效。經由實驗結果發現：(1) IGA實驗與HBGA實驗在收斂代數以及執行時間有明顯差異，消費者能較快從HBGA實驗中得到滿意的結果。(2) IGA實驗與HBGA實驗在對電視櫃成品的滿意程度以及產品組合評分方式的滿意程度有明顯差異，消費者對於HBGA實驗的整體滿意度較高。(3)HBGA透過多人決策，共同腦力激盪的方式，突破區域解，找到更合適的滿意解，且在HBGA中他人的設計具有一定程度的影響力。經由以上結果發現本研究應用HBGA於創意發想和新產品設計中具有高度可行性，並可透過水平行銷方式開發出個人化和客製化之產品。總之，本研究結合顧客價值和滿意度於企業新產品開發流程，創造和傳遞顧客價值的研究，維繫長期有利的顧客關係，且經由顧客滿意和顧客忠誠以達成企業的生存、利潤和成長目標，最後可提昇企業之市場競爭力。

In the past, companies design new products only from the company’s perspective. However, placing the emphasis on Customer Relationship Management, companies should consider customer’s needs and take customer’s value into consideration. Therefore, this study applies the characteristics of intelligent agents with Human-Based Genetic Algorithm to new product evolution and improves success rate for new product entering the market.
This study proposes three models for new product design－idea generation model, product design model and group decision AHP-like concept evaluating module. In the product design phase, this study conducted three experiments: the IGA experiment, HBGA experiment and single HBGA experiment for TV-cabinet combinations design in the furniture industry. The study intends to verify that HBGA could not only solve the human fatigue problem of IGA but also get customer’s satisfactory solutions faster, and reach the goal of group decision making.
The results of this study were as follows:
1. There were significant differences between IGA and HBGA experiments in convergent generation and time spending; the consumers were satisfied faster in HBGA experiment.
2. There were also differences between IGA and HBGA in two aspects: the satisfaction of the product of TV-cabinet goods and the satisfaction of the scores of product combination. Overall, consumers feel more satisfied in HBGA experiments.
3. HBGA, through group decision making and brainstorming, could get through the local optimal solution and get suitable satisfactory solution.
Based on the results of this study, it is feasible for idea generation and new product design based on HBGA to implement and develops customized products. And personalized and customized products can also be made through lateral marketing. In sum, this study combines customer value and satisfaction in the new product design process, creates and maintains long term relationship with customers, and furthermore maintains enterprise’s competitive advantages.

第壹章 緒論
第一節 研究背景與動機
第二節 研究問題
第三節 研究目的
第四節 論文架構與研究流程
第貳章 文獻探討
第一節 新產品開發程序
第二節 群體決策支援系統
第三節 遺傳演算法與交談式遺傳演算法
第四節 以人為基遺傳演算法
第五節 GA在決策制定方面之相關研究
第六節 本章小結
第參章 研究設計
第一節 研究架構
第二節 模組說明
第三節 IGA與HBGA架構設計
第四節 實驗設計
第五節 系統效能測試
第肆章 實驗結果分析
第一節 HBGA創意發想協調模組
第二節 HBGA產品設計協調模組
第三節 群體決策類AHP概念評估模組
第伍章 結論與建議
第一節 研究結論
第二節 研究貢獻
第三節 研究限制
第四節 後續研究建議
參考文獻
附錄一
附錄二

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三、網站資料
1.Human Based Genetic Algorithm, http://www.geocities.com/alex+kosorukoff/hbga/hbga.html, available：2004年11月。