臺灣人文及社會科學引文索引資料庫系統

:::

詳目顯示

回上一頁
第 1 筆 / 總合 1 筆   第一頁 上一頁 下一頁 最後一頁
/1頁
題名：創新動態中的最佳化能力集合轉化
作者：賴宗智
作者(外文)：Tsung-Chih Lai
校院名稱：國立交通大學
系所名稱：資訊管理研究所
指導教授：游伯龍
學位類別：博士
出版日期：2008
主題關鍵詞：習慣領域；能力集合；創新動態；能力集合調整；多目標決策；紅色接單黑色出貨；Habitual Domains；Competence Set Analysis；Innovation Dynamics；Competence Set Adjustment；Multiple Criteria Decision Making；Red in-Black out
原始連結：連回原系統網址new window
相關次數：
  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:0
  • 點閱點閱:44
我們的記憶、觀念、想法、判斷、反應（統稱為念頭和思路）雖然是動態的，但經過一段時間以後，如果沒有重大事件的刺激，會漸漸地穩定下來，而停在一個固定的範圍內。這些念頭和思路的綜合範圍，包括它們的動態和組織，就是我們的習慣領域（habitual domain, HD）。當我們面對一個決策問題時，相對應的存在一個能力集合（competence set, CS），包括能使我們得到滿意解答所須的想法、知識、技能、資源等等。因為能力集合是我們習慣領域針對某一決策問題的投影，如果習慣領域僵化了，我們的能力集合便無法擴展，進而會阻礙創新的展現。若沒有持續不斷地擴展、升級我們的習慣領域與能力集合，我們就很有可能走入決策陷阱或做出錯誤的決策而不自知。本論文基於習慣領域理論及能力集合分析，提出運作領域（working domain）的概念以及創新循環模式（innovation dynamics）。此模式可以使我們的運作領域能更加的靈活、有彈性。接著我們將著眼於創新循環模式中能力集合轉化的部份，討論最佳化能力集合調整問題。給定一個目標解，我們提出能力集合調整模式（competence set adjustment model, CSA model）求得生產參數的最佳調整，使得該目標解得以被達成。當目標解無法被達成時，我們透過二分法（bisection algorithm）或模糊線性規劃（fuzzy linear programming）的方法修正此目標解。最後，我們利用多準則多資源水準限制線性規劃模式（multiple criteria and multiple constraint levels linear programming, MC2LP）探討可變生產參數的線性規劃模式。這些參數包括單位利潤、可用資源以及投入產出參數。在這些參數會隨著投資或時間而改變的情況下，我們將探討如何找到動態最佳解使得「接單時虧損，交貨時獲利」（紅色接單、黑色出貨）的目標得以實現。
Habitual domain (HD) is a collection of ways of thinking, coupled with its formation, interaction and dynamics, which can gradually stabilize as time passes. Unless extraordinary events occur, our thinking process will reach a steady state. For a decision problem E, there exists a corresponding competence set (CS) consisting of ideas, knowledge, skills, and resources to successfully solve the problem. Being a projection of our habitual domains with respect to E, our competence set may not be expanded as our habitual domains get ossified. This can conceal our innovation. Therefore, without continuous expanding and upgrading our HD and CS, we may unconsciously step into decision traps and make wrong decisions. Based on HD theory and CS analysis, the dissertation presented here introduces the concepts of working domain and innovation dynamics. The model of innovation dynamics helps our working domain become more flexible and agile. We, in advance, focus on the transformation of competence set in the innovation dynamics to investigate the problem of optimal adjustment of competence set. The program is formulated into a linear programming model called competence set adjustment model (CSA model). By means of the CSA model, we study how to optimally adjust the relevant coefficients so that a given target solution could be attainable. In case the target is unattainable, we may either utilize the bisection method or the fuzzy linear programming techniques to revise the target as to make it a reachable one. Finally, we utilize multiple criteria and multiple constraint levels linear programming (MC2LP) model and its extended techniques to explore the linear programming models with changeable parameters. The parameters include: unit profit, available resources and input-output coefficients of production function. With those parameters changed with capital investment and/or time, we study how to find dynamic best solutions to make "taking loss at the ordering time and making profit at the time of delivery" feasible. For more general cases we also sketch a generalized mathematical programming model with changeable parameters and control variables.
[1] Chianglin, C. Y., Chen, J. S., and Yu, P. L., “Transforming from A Researcher into A Leader in High-tech Industries”, International Journal of Information Technology & Decision Making, 3, 3, pp. 379-393, 2004.
[2] Yu, P. L., “Working Knowledge Mining by Principles for Deep Knowledge”, International Journal of Information Technology & Decision Making, 5, 4, pp. 729-738, 2006.
[3] Yu, P. L. and Chianglin, C. Y., “Decision Traps and Competence Dynamics in Changeable Spaces”, International Journal of Information Technology & Decision Making, 5, 1, pp. 5-18, 2006.
[4] Yu, P. L. and Chianglin, C. Y., “Games as People Play and How to Form Winning Strategies”, International Journal of Mathematics, Game Theory and Algebra (edited by Dr. L. A. Petrosjan and V. V. Mazalov), 13, 1, pp. 57-80, 2003.
[5] Yu, P. L., “Behavior Bases and Habitual Domains of Human Decision/Behavior – Concepts and Applications”, Multiple Criteria Decision-Making, Theory and Applications (edited by Fandel, G. and Gal, T.), Springer-Verlag, New York, pp. 511-539, 1980.
[6] Yu, P. L., “Habitual Domains”, Operations Research, 39, 6, pp. 869-876, 1991.
[7] Chan, S. J. and Yu, P. L., “Stable Habitual Domains: Existence and Implications”, Journal of Mathematical Analysis and Applications, 110, 2, pp. 469-482, 1985.
[8] Yu, P. L. and Zhang, D., “Competence Set Analysis for Effective Decision Making”, Control-Theory and Advanced Technology, 5, 4, pp. 523-547, 1989.
[9] Yu, P. L. and Zhang, D., “A foundation for competence set analysis”, Mathematical Social Sciences, 20, 3, pp. 251-299, 1990.
[10] Yu, P. L. and Chiang, C. I., “Decision Making, Habitual Domains and Information Technology”, International Journal of Information Technology & Decision Making, 1, 1, pp. 5-26, 2002.
[11] Yu, P. L., Forming Winning Strategies: An Integrated Theory of Habitual Domains, Springer-Verlag, Berlin Heidelberg New York, 1990.
[12] ──, Habitual Domains and Forming Winning Strategies, NCTU Press, Hsinchu, Taiwan, 2002.
[13] ──, Habitual Domains: Freeing Yourself From the Limits on Your Life, Highwater Editions, Shawnee Mission, Kansas, 1995.
[14] ──, Multiple Criteria Decision Making: Concepts, Techniques and Extensions, Plenum, New York, 1985.
[15] Carroll, S. J. and Tosi, H. L., Management By Objectives: Applications and research, The Macmillan Company, New York, 1973.
[16] Baddeley, A. D., Human Memory: Theory and Practice, Allyn & Bacon, 1998.
[17] Baddeley, A. D., and Wilson, B. A., “Prose recall and amnesia: implications for the structure of working memory”, Neuropsychologia, 40, 10, pp. 1737-1743, 2002.
[18] Baddeley, A. D., Working Memory, Oxford University Press, New York, 1986.
[19] Miyake, A. and Shah, P., Models of Working Memory: Mechanisms of Active Maintenance and Executive Control, Cambridge University Press, 1999.
[20] Atkinson, R. C. and Shiffrin, R. M., “Human Memory: A Proposed System and Its Control Processes”, In Spence, K. W. and Spence, J. T. (Eds.), The Psychology of Learning and Motivation: Advances in Research and Theory, Academic Press, New York, 2, pp. 89-195, 1968.
[21] Atkinson, R. C. and Shiffrin, R. M., “The control of short-term memory”, Scientific American, 225, 2, pp. 82-90, 1971.
[22] Olton, D. S., Walker, J. A., and Gage, F. H., “Hippocampal connections and spatial discrimination”, Brain Research, 139, 2, pp. 295-308, 1978.
[23] Olton, D. S., Becker, J. T., and Handelmann, G. E., “Hippocampus, space, and memory”, Behavioral and Brain Sciences, 2, 3, pp. 313-365, 1979.
[24] Baddeley, A. D., and Hitch, G. J., “Working Memory”, In Bower, G. H. (Ed.), The Psychology of Learning and Motivation: Advances in Research and Theory, Academic Press, New York, 8, pp. 47-89, 1974.
[25] Baddeley, A. D., “The episodic buffer: a new component of working memory?”, Trends in Cognitive Science, 4, 11, pp. 417-423, 2000.
[26] Vitruvius, The ten books on architecture, Translated by Morgan M. H., Dover, New York, 1960, pp. 253-254.
[27] Holsapple, C. W., Handbook on Knowledge Management, Springer-Verlag, Berlin Heidelberg New York, 2003.
[28] Grant, G. G., ERP & Data Warehousing in Organizations: Issues and Challenges, IRM Press, 2003.
[29] Stadtler, H. and Kilger, C., Supply Chain Management and Advanced Planning: Concepts, Models, Software, and Case Studies, Springer-Verlag, Berlin Heidelberg New York, 2002.
[30] Zikmund, W. G., McLeod, R. and Gilbert, F. W., Customer Relationship Management: Integrating Marketing Strategy and Information Technology, Wiley, 2002.
[31] Alinsky, S. D., Rules for Radicals, Vintage Books, New York, 1972.
[32] Drucker, P. F., “The Coming of New Organization”, Harvard Business Review on Knowledge Management, Harvard Business School Press, Boston MA, 1998.
[33] Sharkie, R., “Knowledge creation and its place in the development of sustainable competitive advantage”, Journal of Knowledge Management, 7, 1, pp. 20-31, 2003.
[34] Odiorne, S. G., Management By Objectives: A System of Managerial Leadership, Pitman Publishing Corporation, New York, 1965.
[35] Tarantola, A., Inverse Problem Theory: Methods for Data Fitting and Model Parameter Estimation, Elsevier Science Publishing Company Inc., New York, 1987.
[36] Zhang, J. and Liu, Z., “Calculating some inverse linear programming problems”, Journal of Computational and Applied Mathematics, 72, 2, pp. 261-273, 1996.
[37] Zhang, J. and Liu, Z., “A further study on inverse linear programming problems”, Journal of Computational and Applied Mathematics, 106, 2, pp. 345-359, 1999.
[38] Ahuja, K. R. and Orlin, B. J., “Inverse Optimization”, Operations Research, 49, 5, pp. 771-783, 2001.
[39] Troutt, D. M., Tadisina, K. S., Sohn, C., Brandyberry, A. A., “Linear Programming System Identification”, European Journal of Operational Research, 161, 3, pp. 663-672, 2005.
[40] Li, H. L. and Yu, P. L., “Optimal Competence Set Expansion Using Deduction Graphs”, Journal of Optimization Theory and Applications, 80, 1, pp. 75-91, 1994.
[41] Shi, D. S. and Yu, P. L., “Optimal Expansion and Design of Competence Sets with Asymmetric Acquiring Costs”, Journal of Optimization Theory and Applications, 88, 3, pp. 643-658, 1996.
[42] Feng, J. W. and Yu, P. L., “Minimum Spanning Table and Optimal Expansion of Competence Set”, Journal of Optimization Theory and Applications, 99, 3, pp. 655-679, 1998.
[43] Li, H. L., “Technical note: An efficient method for solving linear goal programming problems”, Journal of Optimization Theory and Applications, 90, 2, pp. 465-469, 1996.
[44] Li, H. L., “Solve least absolute value regression problems using modified goal programming techniques”, Computers & Operations Research, 25, 12, pp. 1137-1143, 1998.
[45] Mathews, J. H. and Fink, K. D., Numerical Methods Using MATLAB, 4th ed., Prentice Hall, Upper Saddle River, New Jersey, 2004.
[46] Carlsson, C. and Korhonen, P., “A parametric approach to fuzzy linear programming”, Fuzzy Sets and Systems, 20, 1, pp. 17–30, 1986.
[47] Lai, Y. J. and Hwang, C. L., Fuzzy Mathematical Programming: Methods and Applications, Springer-Verlag, Berlin Heidelberg, 1992.
[48] Nayak, P. R. and Ketteringham, F. M., Breakthroughs!, Pfeiffer & Company, San Diego, CA, 1993.
[49] Bradley, S. P., Hax, A. C. and Magnanti, T. L., Applied Mathematical Programming, Addison-Wesley, Reading, MA, 1997.
[50] Wendell, R. E., “Using bounds on the data in linear programming: The tolerance approach to sensitivity analysis”, Mathematical Programming, 29, 3, pp. 304-322, 1984.
[51] Wendell, R. E., “The tolerance approach to sensitivity analysis in linear programming”, Management Science, 31, 5, pp. 564-578, 1985.
[52] Wendell, R. E., “Tolerance sensitivity and optimality bounds in linear programming”, Management Science, 50, 6, pp. 797-803, 2004.
[53] Hiller, F. S. and Lieberman, G. J., Introduction to Operations Research, 8th ed., McGraw-Hill, New York, 2005.
[54] Gal, T., Postoptimal Analysis, Parametric Programming, and Related Topics, 2nd ed., Walter de Gruyter, Berlin, Germany, 1995.
[55] Seiford, L. and Yu, P. L., “Potential solution of linear system: The multi-criteria multiple constraint level program”, Journal of Mathematical and Analysis and Application, 69, 2, pp. 283-303 ,1979.
[56] Shi, Y., Multiple Criteria and Multiple Constraint Levels Linear Programming: Concepts, Techniques and Application, World Scientific Publishing, Singapore, 2001.
[57] Shi, Y., Yu, P. L. and Zhang, D., “Eliminating Permanently Dominated Opportunities in Multiple-Criteria and Multiple-Constraint Level Linear Programming”, Journal of Mathematical Analysis and Applications, 183, 3, pp. 685-705, 1994.
[58] Zhong, Y. and Shi, Y., “An Interior-Point Approach for Solving MC2 Linear Programming”, Mathematical & Computer Modelling, 34, 3, pp. 411-422, 2001.
[59] Shi, Y. and Liu, Y. H., “Fuzzy Potential Solutions in Multi-Criteria and Multi-Constraint Levels Linear Programming Problems”, Fuzzy Sets and Systems, 60, 2, pp. 163-179, 1993.
[60] Liu, Y. H. and Shi, Y., “A Fuzzy Programming Approach for Solving A Multiple Criteria and Multiple Constraint Level Programming Problem”, Fuzzy Sets and Systems, 65, 1, pp. 117-124, 1994.
[61] Liu, Y., Shi, Y. and Liu, Y. H., “Duality of Fuzzy MC2 Linear Programming: A Constructive Approach”, Journal of Mathematical Analysis and Applications, 194, 2, pp. 389-413, 1995.
[62] Zhong, Y. and Shi, Y., “Duality in Fuzzy Multi-criteria and Multi-constraint Level Linear Programming: A Parametric Approach”, Fuzzy Sets and Systems, 132, 3, pp. 335-346, 2002.
[63] Chiang, C. I. and Yu, P. L., “Competence Set Analysis: An Effective Means to Solve Non-trivial Decision Problem”, Lecture Notes in Economics and Mathematical Systems, 507, pp. 142-151, 2001.
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
:::
無相關著作
 
無相關點閱
 
QR Code
QRCODE

臺灣人文及社會科學引文索引資料庫

目前上線人數：454（臺灣：446，外國：8） ／ 本年度總使用人次：1669892 ／ 訪客人次（自102年09月）：67474291
國家圖書館著作權聲明 Copyright © 2013 All rights reserved.
本館地址: 100201臺北市中山南路20號． 本館地圖及交通資訊．
總機：(02)23619132．最佳瀏覽解析度為1024x768以上