Robust optimization approach for a chance-constrained binary knapsack problem
- Authors
- 한진일; 이경식; 이충목; 최기석; 박성수
- Issue Date
- May-2016
- Publisher
- SPRINGER HEIDELBERG
- Citation
- MATHEMATICAL PROGRAMMING, v.157, no.1, pp.277 - 296
- Journal Title
- MATHEMATICAL PROGRAMMING
- Volume
- 157
- Number
- 1
- Start Page
- 277
- End Page
- 296
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/5635
- DOI
- 10.1007/s10107-015-0931-0
- ISSN
- 0025-5610
- Abstract
- We consider a certain class of chance-constrained binary knapsack problem where each item has a normally distributed random weight that is independent of the other items. For this problem we propose an efficient pseudo-polynomial time algorithm based on the robust optimization approach for finding a solution with a theoretical bound on the probability of satisfying the knapsack constraint. Our algorithm is tested on a wide range of random instances, and the results demonstrate that it provides qualified solutions quickly. In contrast, a state-of-the-art MIP solver is only applicable for instances of the problem with a restricted number of items.
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