On the use of CBR in optimisation problems such as the TSP
On the use of CBR in optimisation problems such as the TSP
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关于 CBR 在 TSP 等优化问题中的使用
DOI：
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发表时间：
1995
期刊：
影响因子：
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通讯作者：
N. Hurley
中科院分区：
文献类型：
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作者：
P. Cunningham;Barry Smyth;N. Hurley
CBR的特殊优势通常被认为是它在弱理论领域的使用，其中解决方案质量被编译成案例并可重用。在本文中，我们探讨了另一种使用CBR优化问题的情况下，高度优化的结构，在一个巨大的高度约束的解决方案空间。我们的分析集中在旅行推销员问题的困难，而不是任何困难与域理论的计算复杂性的问题。我们发现，CBR是很好的生产中等质量的解决方案，在非常快的时间。我们很难让CBR产生高质量的解决方案，因为解决方案质量似乎在适应过程中丢失了。我们还认为，实验与CBR透明的问题，如TSP告诉我们很多方面的CBR，如CBR解决方案的质量，覆盖率的情况下，在案例库提供和实用程序的扩展案例库。
The particular strength of CBR is normally considered to be its use in weak theory domains where solution quality is compiled into cases and is reusable. In this paper we explore an alternative use of CBR in optimisation problems where cases represent highly optimised structures in a huge highly constrained solution space. Our analysis focuses on the Travelling Salesman Problem where difficulty arises from the computational complexity of the problem rather than any difficulty associated with the domain theory. We find that CBR is good for producing medium quality solutions in very quick time. We have difficulty getting CBR to produce high quality solutions because solution quality seems to be lost in the adaptation process. We also argue that experiments with CBR on transparent problems such as the TSP tell us a lot about aspects of CBR such as; the quality of CBR solutions, the coverage that cases in the case-base offer and the utility of extending a case-base.