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Lagrangean heuristics combined with reoptimization for the 0-1 bidimensional knapsack problem

机译:拉格朗日启发法与重新优化相结合的0-1二维背包问题

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摘要

First, this paper deals with lagrangean heuristics for the 0-1 bidimensional knapsack problem. A projected subgradient algorithm is performed for solving a lagrangean dual of the problem, to improve the convergence of the classical subgradient algorithm. Secondly, a local search is introduced to improve the lower bound on the value of the biknapsack produced by lagrangean heuristics. Thirdly, a variable fixing phase is embedded in the process. Finally, the sequence of 0-1 one-dimensional knapsack instances obtained from the algorithm are solved by using reoptimization techniques in order to reduce the total computational time effort. Computational results are presented. (c) 2006 Elsevier B.V. All rights reserved.
机译:首先,本文针对0-1二维背包问题处理了拉格朗日启发式算法。为了解决该问题的拉格朗日对偶,设计了投影次梯度算法,以提高经典次梯度算法的收敛性。其次,引入局部搜索以提高由拉格朗日启发法产生的背包的价值的下限。第三,可变固定阶段被嵌入到该过程中。最后,通过使用重新优化技术来求解从该算法获得的0-1个一维背包实例的序列,以减少总的计算时间。给出了计算结果。 (c)2006 Elsevier B.V.保留所有权利。

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