| Project/Area Number |
15510128
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | Osaka University |
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Principal Investigator |
MORITA Hiroshi Osaka University, Department of Information and Physical Sciences, Professor, 大学院・情報科学研究科, 教授 (60210176)
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| Co-Investigator(Kenkyū-buntansha) |
ISHII Hiroaki Osaka University, Department of Information and Physical Sciences, Professor, 大学院・情報科学研究科, 教授 (90107136)
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| Project Period (FY) |
2003 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2004: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 2003: ¥2,100,000 (Direct Cost: ¥2,100,000)
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| Keywords | Data Envelopment analysis / Efficiency analysis / Regression analysis / Stochastic frontier analysis / Inefficiency / Uncertainty / Design of experiment / Statistical quality control |
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| Research Abstract |
We have studied the evaluation and optimization methods to identify the process inefficiency in social systems and production systems.
1. Development of DEA method for various circumstances
(1) We have shown the properties on the decomposition of inefficiency and multiplier bounds.
(2) We have developed the context-dependent DEA and introduced the slack based measure of efficiency, which provide the appropriate efficiency evaluation and goal for improvement.
(3) We have developed the DEA model to evaluate the efficiency of supply chain performance.
(4) We have shown that DEA can be effectively applied to Pareto evaluation for multiobjective scheduling.
2. Development of inefficiency identification model for statistical method
(1) We have considered the inefficiency identification model to evaluate the quantitative inefficiency by introducing the concept of inefficiency into statistical method.
(2) We have developed the regression model subject to inefficiency. The efficient algorithm to identify the inefficiency gap for multi regression model to deal with multiple input factors.
(3) As an extension to the other statistical method, we have developed the factorial experiment model subject to inefficiency by adopting stochastic frontier analysis.
Other works on the application of DEA method have been studied, such as the index for frontier shift to find the progress of technology as well as performance, the performance index under competitive environment, variable selection scheme by using orthogonal layout. These results will be published after the verification of their effectiveness by using practical data.
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