Studies on statistical approaches in stochastic programming 確率的計画法における統計的手法の研究

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著者

    • 森田, 浩, 1961- モリタ, ヒロシ

書誌事項

タイトル

Studies on statistical approaches in stochastic programming

タイトル別名

確率的計画法における統計的手法の研究

著者名

森田, 浩, 1961-

著者別名

モリタ, ヒロシ

学位授与大学

京都大学

取得学位

工学博士

学位授与番号

乙第7888号

学位授与年月日

1992-05-23

注記・抄録

博士論文

目次

  1. 論文目録 / (0001.jp2)
  2. Contents / p7 (0009.jp2)
  3. Preface / p1 (0006.jp2)
  4. Acknowledgement / p5 (0008.jp2)
  5. Chapter 1. INTRODUCTION / p1 (0011.jp2)
  6. 1.1. Purpose of the Dissertation and Historical Background / p1 (0011.jp2)
  7. 1.2. Brief Review of Stochastic Programming / p3 (0012.jp2)
  8. 1.3. Outline of the Dissertation / p15 (0018.jp2)
  9. Chapter 2. A CONFIDENCE REGION METHOD FOR STOCHASTIC LINEAR PROGRAMMING / p21 (0021.jp2)
  10. 2.1. Introduction / p21 (0021.jp2)
  11. 2.2. Stochastic Linear Programming with an Estimated Right-hand Side / p23 (0022.jp2)
  12. 2.3. A Solution Method / p28 (0025.jp2)
  13. 2.4. Asymptotic Properties / p36 (0029.jp2)
  14. 2.5. An Illustrative Example / p38 (0030.jp2)
  15. 2.6. Stochastic Linear Programming with an Estimated Objective Function / p42 (0032.jp2)
  16. 2.7. A Solution Algorithm for Problem P₁₀ and an Illustrative Example / p44 (0033.jp2)
  17. 2.8. Conclusion / p49 (0035.jp2)
  18. Chapter 3. STOCHASTIC LINEAR PROGRAMMING WITH ESTIMATED CONSTRAINTS / p51 (0036.jp2)
  19. 3.1. Introduction / p51 (0036.jp2)
  20. 3.2. Formulation of the Problem / p53 (0037.jp2)
  21. 3.3. Reverse Convex Programming / p55 (0038.jp2)
  22. 3.4. A Solution Algorithm / p59 (0040.jp2)
  23. 3.5. A Lower Bound of the Optimal Value / p66 (0044.jp2)
  24. 3.6. An Illustrative Example / p70 (0046.jp2)
  25. 3.7. Extension to the Linear Programming Problem with more than One Additional Constraint Including Unknown Coefficients / p72 (0047.jp2)
  26. 3.8. Conclusion / p80 (0051.jp2)
  27. Chapter 4. A CONFIDENCE REGION METHOD FOR A STOCHASTIC LINEAR KNAPSACK PROBLEM / p83 (0052.jp2)
  28. 4.1. Introduction / p83 (0052.jp2)
  29. 4.2. A Stochastic Linear Knapsack Problem / p85 (0053.jp2)
  30. 4.3. A Confidence Region Method for a Stochastic Linear Knapsack Problem / p89 (0055.jp2)
  31. 4.4. Conclusion / p95 (0058.jp2)
  32. Chapter 5. A PROBABILITY MAXIMIZING MODEL OF A STOCHASTIC LINEAR KNAPSACK PROBLEM / p97 (0059.jp2)
  33. 5.1. Introduction / p97 (0059.jp2)
  34. 5.2. A Probability Maximizing Model of a Stochastic Linear Knapsack Problem / p100 (0061.jp2)
  35. 5.3. An Optimal Solution on the Efficient Frontier / p104 (0063.jp2)
  36. 5.4. Conclusion / p111 (0066.jp2)
  37. Chapter 6. AN APPLICATION TO PORTFOLIO SELECTION PROBLEMS / p113 (0067.jp2)
  38. 6.1. Introduction / p113 (0067.jp2)
  39. 6.2. A Block Diagonal Model / p115 (0068.jp2)
  40. 6.3. Index Models / p130 (0076.jp2)
  41. 6.4. Conclusion / p142 (0082.jp2)
  42. Chapter 7. A STOCHASTIC IMPROVEMENT METHOD FOR STOCHASTIC PROGRAMMING / p145 (0083.jp2)
  43. 7.1. Introduction / p145 (0083.jp2)
  44. 7.2. Formulation of the Problem / p147 (0084.jp2)
  45. 7.3. A Stochastic Improvement Method / p152 (0087.jp2)
  46. 7.4. Consistency of the Estimated Region and Convergence of Algorithm SIM / p157 (0089.jp2)
  47. 7.5. Computational Results / p160 (0091.jp2)
  48. 7.6. Conclusion / p161 (0091.jp2)
  49. Chapter 8.CONCLUSION / p165 (0093.jp2)
  50. References / p169 (0095.jp2)
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各種コード

  • NII論文ID(NAID)
    500000086825
  • NII著者ID(NRID)
    • 8000000979097
  • DOI(NDL)
  • NDL書誌ID
    • 000000251139
  • データ提供元
    • NDL-OPAC
    • NDLデジタルコレクション
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