Determining radial efficiency with a large data set by solving small-size linear programs
This paper presents a new algorithm for determining radial efficiency with a large data set by using small-size linear programs (LPs). Instead of trying to “reduce” the size of individual LPs, the proposed algorithm attempts to “control” the size of individual LPs, e.g., no more than 100 data points...
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| Veröffentlicht in: | Annals of operations research 2017-03, Vol.250 (1), p.147-166 |
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| container_title | Annals of operations research |
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| creator | Chen, Wen-Chih Lai, Sheng-Yung |
| description | This paper presents a new algorithm for determining radial efficiency with a large data set by using small-size linear programs (LPs). Instead of trying to “reduce” the size of individual LPs, the proposed algorithm attempts to “control” the size of individual LPs, e.g., no more than 100 data points each time while maintaining the solution quality. The algorithm is specifically designed to address the problem of LP size limitation. From the empirical results, we conclude that the proposed algorithm can converge within a reasonable number of iterations without incurring extra computation time and has savings of up to 60 % of the benchmarks when the data set contains 15,000 points. |
| doi_str_mv | 10.1007/s10479-015-1968-4 |
| format | Article |
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| source | Business Source Complete; Springer Nature - Complete Springer Journals |
| subjects | Algorithms Benchmarks Business and Management Combinatorics Data points Datasets Efficiency Iterative methods Linear programming Mathematical models Operations research Operations Research/Decision Theory Theory of Computation |
| title | Determining radial efficiency with a large data set by solving small-size linear programs |
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