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A penalty algorithm for solving convex separable knapsack problems
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DOI：10.1016/j.amc.2019.124855.png)
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In this paper, we propose a penalized gradient projection algorithm for solving the continuous convex separable knapsack problem, which is simpler than existing methods and competitive in practice. The algorithm only performs function and gradient evaluations, sums, and updates of parameters. The relatively complex task of the algorithm, which consists in minimizing a function in a compact set, is given by a closed formula. The convergence of the algorithm is presented. Moreover, to demonstrate its efficiency, illustrative computational results are presented for medium-sized problems. (C) 2019 Elsevier Inc. All rights reserved.
Keyword:
Separable knapsack problem
Exterior projections
Gradient method
Bregman distances
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期刊
IF:
3.4
论文数:
2.3W
被引数:
3.3W
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