各位老師、同學們大家好!
為提昇台北大學之研究能量與畢業學生工作能力,本校校友講座教授曾國雄親自開授『問題解決之「研究方法」(Research Methods for Problems- Solving)』夏令營(曾國雄講座教授為交通大學終身講座教授,第四屆國家講座、國科會傑出奨三次、國科會特約研究員兩次、暨國科會傑出特約研究員,MCDM Edgeworth- Pareto Award等獎);參加對象為開放校內外有意願「奠定研究基礎」之教師與碩博士班研究生(含大學部三四年級特優培育學生)為原則。課程之初會將『「問題解決(Problems-Solving)」之傳統至最新及未來可能發展的「研究方法(Research Methods)」』以及『如何投稿SSCI/SCI論文之技巧與要點』加以深入淺出的介紹,及其他相關基礎課程之教學分享,爾後本研究室團隊教師及助理群協助【個案討論】或【計算方法】或【軟體操作】等方式,針對各研究方法進行深入探討與實例操作,並以實例說明(如以曾國雄教授實際在SSCI/SCI期刊刊出之論文為例),以帶動台灣學術研究風氣與提昇研究能量。新觀念與新趨勢(New concepts and new trends)之研究方法一開始可能不能馬上聽得懂,不必擔心,不用怕,還是聽下去,多聽幾次!自然就會了!本研究群會在課堂中分享新的議題,而課堂中所分享的議題可以做為文章撰寫的「故事」,找題目實作(邊作邊學,個案分析為以【「故事個案(Story Case)」+「解決問題之研究方法」 結果表達(含「寫作的技巧(Writing Skill)」與「講的技巧( Speech Skill)」),重點在於基本邏輯之思考與推理】),並實作,試著投稿,就會有SSCI/SCI的研究成果產出,且可提昇工作與就業之能力;如果欲達到此研究能量之成果,「天下沒有白吃的午餐」,只要耐心學習,一步一步的達成,相信成果必能「事半功百倍」。有了成果,科技部(原國科會)計畫申請案之通過,就順理其章。
為提昇台北大學之研究能量與畢業學生工作能力,本校校友講座教授曾國雄親自開授『問題解決之「研究方法」(Research Methods for Problems- Solving)』夏令營(曾國雄講座教授為交通大學終身講座教授,第四屆國家講座、國科會傑出奨三次、國科會特約研究員兩次、暨國科會傑出特約研究員,MCDM Edgeworth- Pareto Award等獎);參加對象為開放校內外有意願「奠定研究基礎」之教師與碩博士班研究生(含大學部三四年級特優培育學生)為原則。課程之初會將『「問題解決(Problems-Solving)」之傳統至最新及未來可能發展的「研究方法(Research Methods)」』以及『如何投稿SSCI/SCI論文之技巧與要點』加以深入淺出的介紹,及其他相關基礎課程之教學分享,爾後本研究室團隊教師及助理群協助【個案討論】或【計算方法】或【軟體操作】等方式,針對各研究方法進行深入探討與實例操作,並以實例說明(如以曾國雄教授實際在SSCI/SCI期刊刊出之論文為例),以帶動台灣學術研究風氣與提昇研究能量。新觀念與新趨勢(New concepts and new trends)之研究方法一開始可能不能馬上聽得懂,不必擔心,不用怕,還是聽下去,多聽幾次!自然就會了!本研究群會在課堂中分享新的議題,而課堂中所分享的議題可以做為文章撰寫的「故事」,找題目實作(邊作邊學,個案分析為以【「故事個案(Story Case)」+「解決問題之研究方法」 結果表達(含「寫作的技巧(Writing Skill)」與「講的技巧( Speech Skill)」),重點在於基本邏輯之思考與推理】),並實作,試著投稿,就會有SSCI/SCI的研究成果產出,且可提昇工作與就業之能力;如果欲達到此研究能量之成果,「天下沒有白吃的午餐」,只要耐心學習,一步一步的達成,相信成果必能「事半功百倍」。有了成果,科技部(原國科會)計畫申請案之通過,就順理其章。
「台北大學」夏令營
欲參加者請在2014年7月17日前回覆以便統計,感謝您的協助。
◎『問題解決之「研究方法」』開課地點:台北大學公共事務學院六樓630教室
◎『問題解決之「研究方法」』課程開課時間如下:
欲參加者請在2014年7月17日前回覆以便統計,感謝您的協助。
◎『問題解決之「研究方法」』開課地點:台北大學公共事務學院六樓630教室
◎『問題解決之「研究方法」』課程開課時間如下:
◎『問題解決之「研究方法」』開課時間與地點:
星期一、三下午1:00pm~4:00pm
開課地點:台北大學公共事務學院六樓630教室,新北市三峽區大學路151號
協助教師:劉建浩教授,黃啟祐教授,沈高毅博士,盧明滄博士,莊彥清博士研究生,黃三麟博士研究生,陳建宇博士研究生,黃冠維博士候選人
聯絡人
星期一、三下午1:00pm~4:00pm
開課地點:台北大學公共事務學院六樓630教室,新北市三峽區大學路151號
協助教師:劉建浩教授,黃啟祐教授,沈高毅博士,盧明滄博士,莊彥清博士研究生,黃三麟博士研究生,陳建宇博士研究生,黃冠維博士候選人
聯絡人
Google Scholar
Gwo-Hshiung Tzeng
Distinguished Chair Professor
Research methods for problems-solving: Data Analysis (crisp sets, fuzzy set theory, rough set theory -> statistics and multivariate analysis, evolutionary computation, soft computing, etc.), multiple criteria decision making (MADM and MODM), and so on for applications in the real world problems
Gwo-Hshiung Tzeng
Distinguished Chair Professor
Research methods for problems-solving: Data Analysis (crisp sets, fuzzy set theory, rough set theory -> statistics and multivariate analysis, evolutionary computation, soft computing, etc.), multiple criteria decision making (MADM and MODM), and so on for applications in the real world problems
http://scholar.google.com/citations?user=ZRXOrvQAAAAJ&hl=en
Two New Books, Gwo-Hshiung Tzeng
New Concepts and Trends of MCDM for Tomorrow in Solving Actual Problems
Multiple Attribute Decision Making: Methods and Applications
By Gwo-Hshiung Tzeng & Jih-Jeng Huang (2011), CRC Press, Taylor & Francis Group, A Chapman & Hall Book.
Part I Concepts and Theory of MADM
Analytic Hierarchy Process; Analytic Network Process and Fuzzy Analytic Network Process; Simple Additive Weighting Method; TOPSIS and VIKOR; ELECTRE Method; PROMETHEE Method; Gray Relational Model; Fuzzy Integral Technique; Rough Sets; Structural Model (Interpretive Structural Modeling (ISM) Method, DEMATEL Method, Fuzzy Cognition Maps).
Part II Applications of MADM
AHP: An Application; VIKOR Technique with Applications Based on DEMATEL and ANP; TOPSIS and VIKOR: An Application; ELECTRE: An Application; PROMETHEE: An Application; Fuzzy Integral and Gray Relation: An Application; Fuzzy Integral: An Application; Rough Sets: An Application.
New Concepts and Trends of MCDM for Tomorrow in Solving Actual Problems
Multiple Attribute Decision Making: Methods and Applications
By Gwo-Hshiung Tzeng & Jih-Jeng Huang (2011), CRC Press, Taylor & Francis Group, A Chapman & Hall Book.
Part I Concepts and Theory of MADM
Analytic Hierarchy Process; Analytic Network Process and Fuzzy Analytic Network Process; Simple Additive Weighting Method; TOPSIS and VIKOR; ELECTRE Method; PROMETHEE Method; Gray Relational Model; Fuzzy Integral Technique; Rough Sets; Structural Model (Interpretive Structural Modeling (ISM) Method, DEMATEL Method, Fuzzy Cognition Maps).
Part II Applications of MADM
AHP: An Application; VIKOR Technique with Applications Based on DEMATEL and ANP; TOPSIS and VIKOR: An Application; ELECTRE: An Application; PROMETHEE: An Application; Fuzzy Integral and Gray Relation: An Application; Fuzzy Integral: An Application; Rough Sets: An Application.
Fuzzy Multiple Objective Decision Making
By Gwo-Hshiung Tzeng & Jih-Jeng Huang (2013), CRC Press, Taylor & Francis Group, A Chapman & Hall Book.
Section I Concepts and Theory of Multi-Objective Decision Making
Multi-Objective Evolutionary Algorithms; Goal Programming; Compromise Solution and TOPSIS; De Novo Programming and Changeable Parameters (including Decision Space and Objective Space, called Changeable Spaces); Multi-Stage Programming; Multi-Level Multi-Objective Programming; Data Envelopment Analysis.
Section II Applications of Multi-Objective Decision Making
Motivation and Resource Allocation for Strategic Alliances; Choosing Best Alliance Partners and Allocating Optimal Alliance Resources Using Fuzzy Multi-Objective Dummy Programming Model; Multi-Objective Planning for Supply Chain Production and Distribution Mode: Bicycle Manufacturer; Fuzzy interdependent Multi-Objective Programming; Novel Algorithm for Uncertain Portfolio Selection; Multi-objective Optimal Planning for Designing Relief Delivery Systems; Comparative Productivity Efficiency for Global Telecoms; Fuzzy Multiple Objective Programming in Interval Piecewise Regression Model.
Liou, James J.H. and Tzeng, G.H. (Corresponding author) (2012), Comments on "Multiple criteria decision making (MCDM) methods in economics: An overview", Technological and Economic Development of Economy, 18(4), 672-695.
Abstract. This paper offers comments on a previously published paper, titled “Multiple criteria decision making (MCDM) methods in economics: an overview,” by Zavadskas and Turskis (2011). The paper’s authors made great efforts to summarize MCDM methods but may have failed to consider several important new concepts and trends in the MCDM field for solving actual problems. First, the traditional model assumes the criteria are independently and hierarchically structured; however, in reality, problems are often characterized by interdependent criteria and dimensions and may even exhibit feedback-like effects. Second, relatively good solutions from the existing alternatives are replaced by aspiration levels to fit today’s competitive markets. Third, the emphasis in the field has shifted from ranking and selection when determining the most preferable approaches to performance improvement of existing methods. Fourth, information fusion techniques, including the fuzzy integral method, have been developed to aggregate the performances. Finally, the original fixed resources in multi-objective programming are divided such that both decision and objective spaces are changeable. In this paper, we add new concepts and provide comments that could be thought of as an attempt to complete the original paper.
By Gwo-Hshiung Tzeng & Jih-Jeng Huang (2013), CRC Press, Taylor & Francis Group, A Chapman & Hall Book.
Section I Concepts and Theory of Multi-Objective Decision Making
Multi-Objective Evolutionary Algorithms; Goal Programming; Compromise Solution and TOPSIS; De Novo Programming and Changeable Parameters (including Decision Space and Objective Space, called Changeable Spaces); Multi-Stage Programming; Multi-Level Multi-Objective Programming; Data Envelopment Analysis.
Section II Applications of Multi-Objective Decision Making
Motivation and Resource Allocation for Strategic Alliances; Choosing Best Alliance Partners and Allocating Optimal Alliance Resources Using Fuzzy Multi-Objective Dummy Programming Model; Multi-Objective Planning for Supply Chain Production and Distribution Mode: Bicycle Manufacturer; Fuzzy interdependent Multi-Objective Programming; Novel Algorithm for Uncertain Portfolio Selection; Multi-objective Optimal Planning for Designing Relief Delivery Systems; Comparative Productivity Efficiency for Global Telecoms; Fuzzy Multiple Objective Programming in Interval Piecewise Regression Model.
Liou, James J.H. and Tzeng, G.H. (Corresponding author) (2012), Comments on "Multiple criteria decision making (MCDM) methods in economics: An overview", Technological and Economic Development of Economy, 18(4), 672-695.
Abstract. This paper offers comments on a previously published paper, titled “Multiple criteria decision making (MCDM) methods in economics: an overview,” by Zavadskas and Turskis (2011). The paper’s authors made great efforts to summarize MCDM methods but may have failed to consider several important new concepts and trends in the MCDM field for solving actual problems. First, the traditional model assumes the criteria are independently and hierarchically structured; however, in reality, problems are often characterized by interdependent criteria and dimensions and may even exhibit feedback-like effects. Second, relatively good solutions from the existing alternatives are replaced by aspiration levels to fit today’s competitive markets. Third, the emphasis in the field has shifted from ranking and selection when determining the most preferable approaches to performance improvement of existing methods. Fourth, information fusion techniques, including the fuzzy integral method, have been developed to aggregate the performances. Finally, the original fixed resources in multi-objective programming are divided such that both decision and objective spaces are changeable. In this paper, we add new concepts and provide comments that could be thought of as an attempt to complete the original paper.
Basic New Concepts and Trends of Two New Books for Tomorrow
The basic concept of changeable spaces for achieving aspiration level
The basic concept of changeable spaces for achieving aspiration level
Some listing papers
-- Liou, James J.H. and Tzeng, G.H. (2012), Comments on "Multiple criteria decision making (MCDM) methods in economics: An overview", Technological and Economic Development of Economy, 18(4), 672-695 (SSCI, IF: 5.605, 2011; IF: 3.235, 2012). \
-- Peng, K.H., Tzeng, G.H. (2013), A hybrid dynamic MADM model for problems-improvement in economics and business, Technological and Economic Development of Economy, 19(4), 638–660 (SSCI, IF: 5.605, 2011; IF: 3.235, 2012).
-- Liou, James J.H., Chuang, Y.C., Tzeng, G.H. (2013), “A fuzzy integral-based model for supplier evaluation and improvement, Information Sciences, 266, 199–217 (Impact factor: 3.643, 5-Year Impact Factor: 3.676, 2012).
-- Huang, J.J., Tzeng, G.H. (2014), New thinking of multi-objective programming with changeable space - In search of excellence, Technological and Economic Development of Economy, 20(2), 242-261. (SSCI, IF: 5.605, 2011; IF: 3.235, 2012).
Doi:10.3846/20294913.2013.860931
-- Liou, James J.H. (2013), New concepts and trends of MCDM for tomorrow – in honor of Professor Gwo-Hshiung Tzeng on the occasion of his 70th birthday, Technological and Economic Development of Economy, 19(2), 367–375 (SSCI, IF: 5.605, 2011; IF: 3.235, 2012).
本New Hybrid MCDM model發展之動機、目的與貢獻在於提出:(1)「解決傳統『經濟與統計脫離現實(Economics and Statistics are unrealistic in the real world)』之問題, DEMATEL technique」,(2)「避免「由『爛蘋果中找出最好的蘋果 (Pick the best apple among a barrel of rotten apples),設定「渴望水準(aspiration level)」,modified VIKOR method』」,(3)「避免『頭痛醫頭腳痛醫腳(We need a systematic approach to problem-solving; instead of addressing the symptoms of the problem, we need to identify the sources of the problem),influential network relation map (INRM) by DEMATEL technique』」。
曾國雄講座教授近年來帶領他的研究團隊在解決實際問題之多評準決策領域中提出五大重要的新概念與趨勢之一系列SSCI/SCI期刊論文,最近兩年每年被引用次數在學術Google: 2011 (1531次), 2012 (2080次),其新概念與趨勢列如下:(1)傳統的模型假設各準則為獨立性之分層結構,然而,在現實中,各準則之間存在的問題往往是相互關聯性,甚至可能出現回饋性,他提出解決衡量此相互關聯性與回饋性之影響網路關係的新方法,此可以解決傳統「經濟學與統計學脫離現實的問題」;(2)他提出各方案如何可達到「渇望水準(aspiration level)」的解決方法來替代傳統僅能找出相對較好的解決方案,此方法可以適應解決當今激烈競爭的市場,以避免「由一堆爛蘋果中,找出當中最好的蘋果」;(3)傳統多準則評估只在處理各方案之「排序與選擇(ranking and selection)」問題,他提出如何結合DEMATEL法之影響網路關係圖(influential network relation map, INRM)找出各方案如何以整體系統之「改善(improvement)方式,或改善策略」,可使各準則之績效值皆能提升,使整體系統能達到「渇望水準(aspiration level)」,以避免「腳痛醫腳,頭痛醫頭」的解決方式;(4)在實際社會問題上,資訊融合之績效整合方法,一般是「非(超)加法模型(non-additive/non-super-additive model)」,包含如模糊積分等,1970年代Daniel Kahneman之消費者效用行為實驗結果指出「人類的行為皆不符合加法型」,prospect theory (2002 經濟學Nobel Prize) ;(5)傳統多目標之數學規劃,常在固定資源限制條件下(決策空間),找出多目標Pareto最適解(目標空間),實際問題上,「決策空間」與「目標空間」都可變的,曾傑出講座教授以不同的思考方式,決策者為追求「渇望水準(aspiration level)」的情況下(目標空間可變),如何改變「決策空間」呢?如何在人力資源擴展能力集合呢?如何提昇效率改變限制條件之參變數呢?依此理念提出「可變空間(含「決策空間」與「目標空間」都可變的)」之多目標規劃法。此劃時代新觀念,未來「研究方法之趨勢如何鬆解傳統之假設/假說,使之更符合解決複雜之實務問題」,見解創新,近年來所發展出「新混合式MCDM模型」之新方法,為具劃時代學術與實用之價值。
-- Liou, James J.H. and Tzeng, G.H. (2012), Comments on "Multiple criteria decision making (MCDM) methods in economics: An overview", Technological and Economic Development of Economy, 18(4), 672-695 (SSCI, IF: 5.605, 2011; IF: 3.235, 2012). \
-- Peng, K.H., Tzeng, G.H. (2013), A hybrid dynamic MADM model for problems-improvement in economics and business, Technological and Economic Development of Economy, 19(4), 638–660 (SSCI, IF: 5.605, 2011; IF: 3.235, 2012).
-- Liou, James J.H., Chuang, Y.C., Tzeng, G.H. (2013), “A fuzzy integral-based model for supplier evaluation and improvement, Information Sciences, 266, 199–217 (Impact factor: 3.643, 5-Year Impact Factor: 3.676, 2012).
-- Huang, J.J., Tzeng, G.H. (2014), New thinking of multi-objective programming with changeable space - In search of excellence, Technological and Economic Development of Economy, 20(2), 242-261. (SSCI, IF: 5.605, 2011; IF: 3.235, 2012).
Doi:10.3846/20294913.2013.860931
-- Liou, James J.H. (2013), New concepts and trends of MCDM for tomorrow – in honor of Professor Gwo-Hshiung Tzeng on the occasion of his 70th birthday, Technological and Economic Development of Economy, 19(2), 367–375 (SSCI, IF: 5.605, 2011; IF: 3.235, 2012).
本New Hybrid MCDM model發展之動機、目的與貢獻在於提出:(1)「解決傳統『經濟與統計脫離現實(Economics and Statistics are unrealistic in the real world)』之問題, DEMATEL technique」,(2)「避免「由『爛蘋果中找出最好的蘋果 (Pick the best apple among a barrel of rotten apples),設定「渴望水準(aspiration level)」,modified VIKOR method』」,(3)「避免『頭痛醫頭腳痛醫腳(We need a systematic approach to problem-solving; instead of addressing the symptoms of the problem, we need to identify the sources of the problem),influential network relation map (INRM) by DEMATEL technique』」。
曾國雄講座教授近年來帶領他的研究團隊在解決實際問題之多評準決策領域中提出五大重要的新概念與趨勢之一系列SSCI/SCI期刊論文,最近兩年每年被引用次數在學術Google: 2011 (1531次), 2012 (2080次),其新概念與趨勢列如下:(1)傳統的模型假設各準則為獨立性之分層結構,然而,在現實中,各準則之間存在的問題往往是相互關聯性,甚至可能出現回饋性,他提出解決衡量此相互關聯性與回饋性之影響網路關係的新方法,此可以解決傳統「經濟學與統計學脫離現實的問題」;(2)他提出各方案如何可達到「渇望水準(aspiration level)」的解決方法來替代傳統僅能找出相對較好的解決方案,此方法可以適應解決當今激烈競爭的市場,以避免「由一堆爛蘋果中,找出當中最好的蘋果」;(3)傳統多準則評估只在處理各方案之「排序與選擇(ranking and selection)」問題,他提出如何結合DEMATEL法之影響網路關係圖(influential network relation map, INRM)找出各方案如何以整體系統之「改善(improvement)方式,或改善策略」,可使各準則之績效值皆能提升,使整體系統能達到「渇望水準(aspiration level)」,以避免「腳痛醫腳,頭痛醫頭」的解決方式;(4)在實際社會問題上,資訊融合之績效整合方法,一般是「非(超)加法模型(non-additive/non-super-additive model)」,包含如模糊積分等,1970年代Daniel Kahneman之消費者效用行為實驗結果指出「人類的行為皆不符合加法型」,prospect theory (2002 經濟學Nobel Prize) ;(5)傳統多目標之數學規劃,常在固定資源限制條件下(決策空間),找出多目標Pareto最適解(目標空間),實際問題上,「決策空間」與「目標空間」都可變的,曾傑出講座教授以不同的思考方式,決策者為追求「渇望水準(aspiration level)」的情況下(目標空間可變),如何改變「決策空間」呢?如何在人力資源擴展能力集合呢?如何提昇效率改變限制條件之參變數呢?依此理念提出「可變空間(含「決策空間」與「目標空間」都可變的)」之多目標規劃法。此劃時代新觀念,未來「研究方法之趨勢如何鬆解傳統之假設/假說,使之更符合解決複雜之實務問題」,見解創新,近年來所發展出「新混合式MCDM模型」之新方法,為具劃時代學術與實用之價值。