来源类型 | Research Reports
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规范类型 | 报告
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来源ID | RR-270-A/OSD
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| Portfolio Optimization by Means of Multiple Tandem Certainty-Uncertainty Searches: A Technical Description |
| Brian G. Chow
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发表日期 | 2013
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出版年 | 2013
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页码 | 70
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语种 | 英语
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结论 |
Transparent Reasoning Is Used to Design the Search Schemes- The approach is to use transparent reasoning, as opposed to mathematical formulas, to design search schemes or algorithms to find the global optimum and not get trapped at one of the local optima.
- This approach relies on arguments from devil's advocates to uncover the shortcomings of an algorithm in terms of why under certain situations it will not lead to the global optimum.
These Reasonable Search Algorithms Are Easy to Understand- Implementing search algorithms amounts to creating a flow chart and does not require the use of complicated mathematics or formulas; as a result, the approach allows for adoption by analysts and organizations that possess different skill sets. This approach based on reasoning rather than mathematics can open a new way for drawing in talents from the nonmathematical world to devise search schemes to tackle this very difficult task of optimization under uncertainty. Experience with this approach has been good.
- Each of the algorithms developed in this paper takes minutes or hours to find the optimal solution.
- The research behind this new search approach and the multiple algorithms that go with it was conducted as part of a series of previously released RAND studies by Brian G. Chow, Richard Silberglitt, Scott Hiromoto, Caroline Reilly and Christina Panis: Toward Affordable Systems II: Portfolio Management for Army Science and Technology Programs Under Uncertainties (2011) and Toward Affordable Systems III: Portfolio Management for Army Engineering and Manufacturing Development Programs (2012).
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主题 | Cyber and Data Sciences
; Linear Programming
; Military Acquisition and Procurement
; Military Budgets and Defense Spending
; Modeling and Simulation
; Operations Research
; Optimization Heuristics
; Optimization Modeling
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URL | https://www.rand.org/pubs/research_reports/RR270.html
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来源智库 | RAND Corporation (United States)
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资源类型 | 智库出版物
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条目标识符 | http://119.78.100.153/handle/2XGU8XDN/107476
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推荐引用方式 GB/T 7714 |
Brian G. Chow. Portfolio Optimization by Means of Multiple Tandem Certainty-Uncertainty Searches: A Technical Description. 2013.
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