The performance of heuristic algorithms for combinatorial optimization is often sensitive to problem instances. In extreme cases, a specialized heuristic algorithm may perform exceptionally well on a particular set of...
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The performance of heuristic algorithms for combinatorial optimization is often sensitive to problem instances. In extreme cases, a specialized heuristic algorithm may perform exceptionally well on a particular set of instances while fail to produce acceptable solutions on others, Such a problem-sensitive nature is most evident in algorithms for combinatorial optimization problems such as job shop scheduling, vehicle routing, and cluster analysis. This paper proposes a formal method for comparing and selecting heuristic algorithms (or equivalently, different settings of a same algorithm) given a desired confidence level and a particular set of problem instances. We formulate this algorithm comparison problem as a stochastic optimization problem. Two approaches for stochastic optimization, Ordinal Optimization and Optimal Computing Budget Allocation are applied to solve this algorithm selection problem. Computational testing on a set of statistical clustering algorithms in the IMSL library is conducted. The results demonstrate that our method can determine the relative performance of heuristic algorithms with high confidence probability while using a small fraction of computer times that conventional methods require.
This paper studies different methods proposed so far for segmentation evaluation. Most methods can be classified into three groups: the analytical, the empirical goodness and the empirical discrepancy groups. Each gro...
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This paper studies different methods proposed so far for segmentation evaluation. Most methods can be classified into three groups: the analytical, the empirical goodness and the empirical discrepancy groups. Each group has its own characteristics. After a brief description of each method in every group, some comparative discussions about different method groups are first carried out. An experimental comparison for some empirical (goodness and discrepancy) methods commonly used is then performed to provide a rank of their evaluation abilities. In addition, some special methods are also discussed. This study is helpful for an appropriate use of existing evaluation methods and for improving their performance as well as for systematically designing new evalution methods. Copyright (C) 1996 Pattern Recognition Society. Published by Elsevier Science Ltd.
Although data compression has been studied for over 30 years, many new techniques are still evolving. There is considerable software available that incorporates compression schemes and archiving techniques. The U. S. ...
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Although data compression has been studied for over 30 years, many new techniques are still evolving. There is considerable software available that incorporates compression schemes and archiving techniques. The U. S. Navy is interested in knowing the performance of this software. This thesis studies and compares the software. The testing files consist of the file types specified by the U. S. Naval Security Detachment at Pensacola, Florida.
Various parallel implementations of algorithms for the QR decomposition of a matrix are compared using shared memory multiprocessors. algorithms based on both Givens and Householder transformations are considered. A n...
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Various parallel implementations of algorithms for the QR decomposition of a matrix are compared using shared memory multiprocessors. algorithms based on both Givens and Householder transformations are considered. A number of parallelisation techniques are used with particular emphasis on algorithms which allocate work to tasks dynamically. The results indicate that one version is significantly better than the others.
The function of a treatment planning program is to graphically simulate radiation dose distributions from proposed radiation therapy treatments. While many such programs are available which provide this much needed se...
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The function of a treatment planning program is to graphically simulate radiation dose distributions from proposed radiation therapy treatments. While many such programs are available which provide this much needed service, none addresses the question of how to intercompare calculation and display techniques. A program system designed for support of research efforts, particularly development and testing of new calculation algorithms, is described. The system emphasizes a modular flexible structure, enabling programs to be developed somewhat as interchangeable parts. The multiple variants of a calculation algorithm can be compared without undue software overhead or additional data management. Unusual features of the system include extensive use of command procedures, logical names and a structured language (PASCAL). These features are described along with other implementation details. Obstacles, limitations and future applications are also discussed.
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