Journal article
Efficient Algorithms and Implementations for Optimizing the Sum of Linear Fractional Functions, with Applications
Journal of combinatorial optimization, Vol.9(1), pp.69-90
02/2005
DOI: 10.1007/s10878-005-5485-2
Abstract
This paper presents an improved algorithm for solving the sum of linear fractional functions (SOLF) problem in 1-D and 2-D. A key subproblem to our solution is the off-line ratio query (OLRQ) problem, which asks to find the optimal values of a sequence of m linear fractional functions (called ratios), each ratio subject to a feasible domain defined by O(n) linear constraints. Based on some geometric properties and the parametric linear programming technique, we develop an algorithm that solves the OLRQ problem in O((m+n)log (m+n)) time. The OLRQ algorithm can be used to speed up every iteration of a known iterative SOLF algorithm, from O(m(m+n)) time to O((m+n)log (m+n)), in 1-D and 2-D. Implementation results of our improved 1-D and 2-D SOLF algorithm have shown that in most cases it outperforms the commonly-used approaches for the SOLF problem. We also apply our techniques to some problems in computational geometry and other areas, improving the previous results.
Details
- Title: Subtitle
- Efficient Algorithms and Implementations for Optimizing the Sum of Linear Fractional Functions, with Applications
- Creators
- Danny Chen - Department of Computer Science and Engineering University of Notre Dame Notre Dame IN 46556 USAOvidiu Daescu - Department of Computer Science University of Texas at Dallas Richardson TX 75080 USAYang Dai - Department of Bioengineering (M/C 063) University of Illinois at Chicago Chicago IL 60607 USANaoki Katoh - Department of Architecture and Architectural Systems, Graduate School of Engineering Kyoto University Katsura Nishikyo-ku Kyoto JapanXiaodong Wu - Department of Computer Science University of Texas-Pan American 1201 W. University Drive Edinburg TX 78541 USAJinhui Xu - Department of Computer Science and Engineering State University of New York at Buffalo Buffalo NY 14260 USA
- Resource Type
- Journal article
- Publication Details
- Journal of combinatorial optimization, Vol.9(1), pp.69-90
- DOI
- 10.1007/s10878-005-5485-2
- ISSN
- 1382-6905
- eISSN
- 1573-2886
- Publisher
- Kluwer Academic Publishers; Boston
- Language
- English
- Date published
- 02/2005
- Academic Unit
- Electrical and Computer Engineering; Radiation Oncology
- Record Identifier
- 9984047984302771
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